ADAPT Teaming Profiles
Thank you for showing an interest in ARPA-H’s ADvanced Analysis for Precision cancer Therapy (ADAPT) program. This page is designed to help facilitate connections between prospective proposers. If either you or your organization are interested in teaming, please submit your information via the form below. Your details will then be added to the list below, which is publicly available.
ADAPT anticipates that teaming will be necessary to achieve the goals of the program. Prospective performers are encouraged (but not required) to form teams with varied technical expertise to submit a proposal to the ADAPT solicitation. For questions, please visit the ADAPT portal.
Please note that by publishing the teaming profiles list, ARPA-H is not endorsing, sponsoring, or otherwise evaluating the qualifications of the individuals or organizations included here. Submissions to the teaming profiles list are reviewed and updated periodically.
Teaming Profiles List
To narrow the results in the Teaming Profiles List, please use the input below to filter results based on your search term. The list will filter as you type.
| Organization name | Point of contact name | Point of contact email | Provide an additional point of contact for your organization's representative (email only) | Location | In 200 words or less, describe your organization's current research focus areas | In 200 words or less, tell us what your organization is looking for in potential teaming partners | Which technical areas within ADAPT does your organization have the capacity to address? |
| Datavant, Inc. | Emma Wyllie | emmawyllie@datavant.com | Ed Pompili, ed@datavant.com | Phoenix, Arizona | Datavant works with over 500 institutions to connect health data in ways that preserve patient privacy. Our mission is to connect the world’s health data to improve patient outcomes. A network of healthcare and life sciences companies, non-profits, and government entities utilize our common infrastructure for the safe exchange and linking of patient-level health information, including a range of oncology-related data. Many of our partners in the life sciences use our technology to leverage real world evidence in the entire clinical research life cycle. Additionally, our clinical trial tokenization offering promotes the linkage of clinical trial data to real world data (RWD) for enriched insight. Datavant facilitates linking clinical trial data to the full patient clinical record and more than 600 RWD partners. | Datavant provides a linkage solution to facilitate development of longitudinal patient datasets. Standardly we work with systems integrators and platform solution providers, but are open to discussions with any potential partners. Datavant works predominately in a subcontractor capacity on these multifaceted opportunities. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| Via Scientific Inc. | Alper Kucukural | alper@viascientific.com | jim@viascientific.com | Cambridge, MA | Via Scientific focuses on creating an intuitive and powerful bioinformatics platform, Via Foundry, aimed at simplifying pipeline design, development, and maintenance. It facilitates analysis and management of large sample quantities on various environments like HPC, cloud services, or personal workstations. The platform offers seamless Nextflow pipeline integration, drag-and-drop interface for easy pipeline creation, and supports execution across diverse executors. Additionally, it provides tools for efficient metadata tracking, reproducible and reusable data analysis, including a report section and interactive applications for thorough data exploration supported with various AI models. Via Foundry caters to a broad user base, from bench biologists to expert bioinformaticians, requiring varying levels of programming knowledge. | Via Scientific seeks teaming partners with a strong interest in bioinformatics and computational biology, and bench scientist who bring innovative ideas for simplifying and accumulating complex data analyses for all scientists. Partners with expertise in developing user-friendly software tools, a commitment to advancing scientific research through technology, and a shared vision for making bioinformatics accessible to a broader range of scientists, including those at the bench without extensive computational background, would be highly valued. | TA3: Treatment and analysis platform;TA2: Evolutionary clinical trial;TA1: Therapy recommendation techniques; |
| Fraley Lab, University of California San Diego | Stephanie Fraley | sifraley@ucsd.edu | m1flores@ucsd.edu | La Jolla, CA | The Fraley Lab at UC San Diego has a current research interest in studying the effects of tumor extracellular matrix (ECM) changes on tumor cell transcriptional states and response to therapies. More specifically, we have begun linking tumor ECM characteristics in patient-derived xenograft/organoid models to therapeutic susceptibilities and have been able to recapitulate certain patient tumor states in cell lines by using specific 3D culture techniques. We believe our ECM-centric expertise and perspective would be a valuable addition to technical area 1, which includes multi-modal data fusion, resistant trait modeling, and development of biomarkers to predict drug response. We primarily focus on breast cancer, but have recently expanded into pancreatic cancer. | We are looking for teaming partners that are aiming to generate well-annotated multi-modal datasets and are willing to enable us to contribute additional ECM-centric data (composition, architecture, physical properties) to those datasets. We are also interested in spatial omics analyses, with a focus on regions of tumors where cells contact specific ECM regimes. | TA1: Therapy recommendation techniques; |
| University of California, Santa Cruz | Daniel Kim | daniel.kim@ucsc.edu | Santa Cruz, CA | Daniel Kim's laboratory at the University of California, Santa Cruz is focused on developing advanced RNA liquid biopsy technology for tracking tumor changes before, during, and after treatment in a minimally invasive way using blood plasma. The Kim Lab has developed an RNA liquid biopsy platform technology called COMPLETE-seq (Reggiardo et al. Nature Biomedical Engineering 2023) that comprehensively profiles the cell-free RNA transcriptome by characterizing all of the circulating full-length protein-coding RNA, long non-coding RNA, and repetitive RNA, which they then use as features for disease classification using machine learning/AI. The Kim Lab leverages both short-read and long-read sequencing technology, as well as advanced bioinformatic approaches, to discover and more fully understand cancer biomarkers of tumor evolution and therapy resistance, which will enable clinicians to more effectively treat cancer patients in the future. | The Kim Lab at UC Santa Cruz is seeking clinician partners who are treating cancer patients and can provide blood samples before, during, and after treatment, which we would then profile using our RNA liquid biopsy technology to discover and develop cancer biomarkers of tumor evolution, drug response, and therapy resistance. | TA1: Therapy recommendation techniques; | |
| UT Southwestern Medical Center/ Kidney Cancer Program | James Brugarolas MD PhD, Program Director | james.brugarolas@utsouthwestern.edu | kcpcoord@utsw.edu | Dallas, Tx | As one of two kidney cancer programs recognized with a SPORE award from NCI, we seek to translate discoveries into improvements for patients. Our work has led to a molecular genetic classification of the most common kidney cancer type, the identification of prognostic biomarkers (and of a biological rationale for poorly understood clinical biomarkers), the development of IND-enabled novel molecular imaging probes, the identification and therapeutic exploitation of the first core dependency going from gene discovery to an FDA approved first-in-class drug, and the development and prospective evaluation of novel radiation applications. Leading these developments are multidisciplinary teams of clinical experts (urology, oncology, radiation oncology, radiology and pathology) and basic researchers (>50 labs) making up one of the largest such efforts worldwide. We are supported by a state-of-the-art infrastructure including a live tumor biobank (>1,200 tumors preserved live and >250 PDX models representing the diversity of our combined private and county hospital clinical practice) and an interconnecting self-updating database linked to clinical/pathological information (>5000 patients) and genomics (>1000 WES and RNAseq). These advances are enabled by a large, invested, patient population who understands our mission, eagerly participates in clinical trials, and donates their information and samples. | We are interested in partnering with organizations with shared goals that can complement our efforts where there may be opportunities for synergism. Examples include companies developing precision medicine tools (in particular those focusing on tissue and imaging-based biomarkers, but also those evaluating circulating biomarkers), companies advancing generative AI, and pharmaceutical companies developing drugs for kidney cancer. We are particularly interested in industry partners seeking to leverage our institutional capabilities including our cyclotron program enabling drug labeling to better understand drug properties and more precisely tailor them to patients. Having provided a proof-of-principle in both preclinical models and in a phase I trial for tumor-targeted siRNA therapeutics, we are also interested in gene therapy approaches. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| NYU Langone Health | Marcin Imielinski | marcin.imielinski@nyulangone.org | Laura.Alice@nyulangone.org | New York, New York | Clinical cancer whole genome sequencing for diagnosis, MRD detection, and treatment | Academic cancer centers with near term interest in building a clinical-grade (ie CLIA, CLEP, FDA) cancer whole genome sequencing platform in their health system looking to work together in a network to set / shape the standards of practice in this new era of whole genome molecular oncology. This includes developing practice-changing therapeutic clinical trials to explore concrete insurance-reimbursable clinical applications of WGS. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| Onc.AI | Akshay Nanduri | ananduri@onc.ai | akshaynanduri@gmail.com | San Carlos, California | Onc.AI has assembled one of the largest multi-modal real-world datasets focused on immuno-oncology. Our data asset includes patients longitudinal diagnostic imaging scans (CT, PET-CT, MRI), labs, pharmacy, EMR, demographics and genomics/pathology reports. We have curated this data asset by labeling each tumor, characterizing response to PD-1 checkpoint inhibitors (growth per RECIST or volume, new lesions) and are building radiomic Deep Learning models that predict response to therapy. We believe that radiomics is a crucial component to adaptive therapy and look forward to engaging with potential partners on this proposal. | We are eager to partner with institutions that have access to large clinical trials or RWD (with diagnostic imaging) and are interested in demonstrating the potential of radiomics for precision oncology and therapy adaptation. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial; |
| MD Anderson | Xiling Shen | xiling.shen@terasaki.org | Houston, Tx | As the largest cancer center, we at MD Anderson perform basic, translational, and clinical research. Our team comprise national's leading GI oncology physicians, biomedical engineers and computational scientists. Our team pioneered circulating tumor DNA assays and functional patient-derived micro-organoid assays. What sets us apart is our capability to design functional and precision clinical trails with large patient volume. | New technology that potentially complements the current team's capabilities. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; | |
| Douglass Lab, University of Georgia | Eugene Douglass | eugene.douglass@uga.edu | ed29157@uga.edu | Athens, GA | The Douglass laboratory develops computational methods to better understand spatial transcriptomic datasets with an emphasis on emerging single-cell resolution technologies: CosMx (Nanostring) and Xenium (10xGenomics). Our methods focus on charactering cell-cell communication within tumor-tissue samples to better understand cancer-stromal-immune interactions that affect response and resistance to current chemotherapy/immunotherapy combinations . A critical feature of our algorithms is they use physical laws to improve the performance of our statistical inferences (by adding bias based on prior knowledge). In addition, as physical laws define clear mechanistic hypotheses, our methods are enabling the development of "Google-Maps" type graphic interfaces to enable non-computational investigators to easily explore the “cancer-immune battlefield maps" that spatial transcriptomic technologies provide. | We are looking for clinical pathologists or cancer-immunologists who are interested in applying spatial-transcriptomic technologies (GeoMx, Visium,CosMx, Xenium, etc.) to tumor-tissue samples in parallel to standard histological methods. | TA1: Therapy recommendation techniques;TA3: Treatment and analysis platform; |
| NYU Langone Health | Matija Snuderl, MD | matija.snuderl@nyulangone.org | flavia.camacho@nyulangone.org | New York, NY | Cancer epigenetics and DNA methylation. We utilize whole genome DNA methylation profiling of cancers from all organ sites to dissect epigenetic signatures of primary tumors, epigenetic switch in metastasis and epigenetic adaptation of tumor cells by microenvironment. Our database includes more than 5,000 human tumor samples with DNA methylation and clinical data. | How cancer genetic heterogeneity and tumor stroma interaction including mesenchymal cells and immune cells influence cancer epigenetics. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| OMAPiX Inc | Mridula Iyer | mridula.iyer@omapix.com | nachiket.kashikar@omapix.com | Stanford, CA | OMAPiX is on a mission to improve patient outcomes in precision oncology by leveraging best-in-class spatial multiomics technologies and data analytics. Spatial transcriptomics and proteomics provide critical data that allow us to have the deepest understanding of tumor microenvironment and heterogeneity. We are a team of industry-leading spatial omics experts, and probably the only company that has mastered end-to-end spatial omics data generation and analytics. We leverage leading technology platforms to generate high-quality spatial transcriptomics and proteomics data. This allows us to design complex programs for our partners for multi modal data analysis using our custom data analysis pipeline. Through our research, we enable new target discovery, complex intra- and inter-tumoral heterogeneity, investigation of immune tumor cross talk, and identification of new biomarkers. One of the major programs that we have undertaken is to analyze new spatial biomarkers for antibody-drug conjugate (ADC) therapy for advancing precision care in cancer aimed to improve patient outcomes. Our projects in Oncology are focused on developing novel standardized approach to integrate multi-modal data for downstream companion Dx characterized by unique spatial molecular signatures. | We look forward to partner with entities that can provide below four things: (1) access to patient samples for retrospective analysis of responders/non responders. (2) extend to prospective clinical studies (3) expertise to develop AI/ML models (4) design companion Dx panels for targeted therapy. Our program will enhance spatial resolution in samples of responders and non-responders to cancer therapy. Such collaborations will open new opportunities for discovering novel biological knowledge, biomarkers, and therapeutic targets. Our goal is to eventually develop a companion Dx to help identify crucial spatial information in patients. This will enable recruitment to trials more efficiently and effectively. We can eventually identify the right patients for treatment. | TA1: Therapy recommendation techniques; |
| BioCytics, Inc | Brent Dixon | bdixon@biocytics.com | rwarin@biocytics.com | Huntersville, NC | BioCytics, Inc., founded in 2005, is a health technology company with a focused mission to directly apply living cells in clinical trials as affordable individualized immune cellular therapies manufactured at the PoC. It is the only independent, privately held, warm-chain PoC cellular manufacturing facility in the US. Its affiliate, Carolina BioOncology Institute, PLLC (CBOI) is co-located adjacent to BioCytics Good Manufacturing Practices (GMP) facility. BioCytics primary research is focused on its proprietary Warm-Chain Point-of-Care (PoC) Manufacturing and Individualized Autologous Adaptive Cellular Therapy (AACT) Platform. This platform is focused on identifying the most effective patient specific/individualized immune cell therapy, by leveraging circulating tumor cells/cell clusters. BioCytics is fully vertically integrated Human Applications Laboratory (HAL), capable of producing maximally fit immune cells for optimized solid tumor agnostic (pan-cancer) therapeutics. BioCytics-CBOI infrastructure forms a fully integrated warm-chain PoC manufacturing platform where a patient’s immune cells can be collected, by blood draw or leukapheresis, immediately transferred to the adjacent GMP compliant HAL for AACT manufacturing. BioCytics HAL is a revolutionary manufacturing platform key to the production of autologous non-genetically modified cells with the highest specificity and functionality. BioCytics partners with cancer researchers to advance cancer research through its biospecimen sourcing efforts. | Leukapheresis derived circulating tumor cells (CTCs), tumor derived cell clusters (TDCCs) and patient derived tumor organoids (PDTOs). GMP process optimization and scale up for manufacturing clinical trial cell therapy investigational product. CDMO including IND drafting and submission to FDA for phase 1 clinical trials. Clinical trial site for pan-cancer solid tumor cell therapies. BioCytics offers translational research services leveraging its cellular biology labs including advanced equipment including flow cytometry, video microscopy, impedance cytotoxicity assays and custom assays. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| BostonGene Corporation | Krystle Nomie | krystle.nomie@bostongene.com | anna.love@bostongene.com | Waltham, MA | BostonGene Corporation is a precision diagnostics company specializing in multiparametric biomarker discovery. Our fully integrated multi-omics approach capitalizes on our in-house tissue- and blood-based profiling platforms, capable of characterizing the tumor microenvironment and global immune status. BostonGene leverages ctDNA, ctRNA, Immunoprofiling, multiplex immunofluorescence, AI pathology, whole exome, and whole transcriptome sequencing technologies to drive innovation. Our group developed a multi-parametric biomarker combining the tumor microenvironment subtype and tumor mutational burden, the Tumor Immunity PortraitTM, which is predictive of immunotherapy response in non-small cell lung, bladder, melanoma, and gastric cancers (PMID: 34019806). KassandraTM is an in-house cellular deconvolution algorithm designed to reconstruct the tumor microenvironment from bulk RNA-seq data (PMID: 35944503), while Helenus evaluates gene expression from the malignant cells. KassandraTM and Tumor Immunity PortraitTM are incorporated in our clinical laboratory-developed test, the Tumor PortraitTM, which additionally leverages our proprietary clinical decision-making support tools, Hippocrates and digitized NCCN Guidelines®. Ongoing work includes establishing RNA-seq gene expression thresholds for immunohistochemistry biomarkers, including antibody-drug conjugates. BostonGene’s research aims to support clinical decision-making and maximize therapeutic response rates by generating treatment recommendations tailored to the patient’s unique molecular and immune biomarker profile. | BostonGene actively engages in innovative research with academic and pharmaceutical partners. For ADAPT, BostonGene is seeking teaming partners who share our vision for advancing precision oncology with a biomarker-driven approach. With our expertise in integrative multi-omics technologies, database development, and bioinformatics, ideal academic partners have access to diverse patient cohorts for multi-parametric biomarker discovery, model training, and adequate validation and a strong track record in clinical research. For industry partners, BostonGene is seeking companies committed to developing biomarker-driven approaches for clinical trial patient selection. We value partnerships that complement our capabilities to accelerate the development and adoption of innovative diagnostic solutions in oncology. | TA1: Therapy recommendation techniques;TA3: Treatment and analysis platform; |
| Baylor College of Medicine | Tao Wu | tao.wu@bcm.edu | xiaomei.zhan@bcm.edu | Houston, TX | In the human genome, transposable elements (TE) contribute about 50%. Recently, emerging studies have shown that these genomic "dark matter" may serve as the diagnostic marker or treatment target in cancer diagnosis and clinical trials. Our lab employs state-of-the-art molecular and cell biology strategies to investigate TEs' functional mechanisms underpinning cancer therapeutic resistance. Moreover, we collaborate with the machine-learning team and have developed new analysis pipelines for these repetitive elements, which is a bottleneck in TE research. In our study, we have confirmed one type of human endogenous retrovirus (HERV) plays a fundamental role in cancer cell adaptation through chemo-treatment. | We are searching for the pre-clinical and clinical trails collaboration, who wants to target these TEs. Also, we are looking for the clinical data analysis collaboration on this topic. | TA1: Therapy recommendation techniques; |
| Shreis Scalene Sciences LLC | Meena Augustus | maugustus@shreis.com | john.augustus@shreis.com | Gaithersburg, MD | Innovative, non-invasive cancer therapeutic platform technology using tissue engineering. 1. Non-invasive cancer treatment for all solid tumors, (adult and pediatric, including gliomas/GBM), with clinical response, good quality of life and pain relief without the use of opioids 2. Non-invasive targeted cancer drug delivery to reduce collateral damage and improve compliance to cancer chemotherapy. | Infrastructural support and participation of medical, nursing and technical professionals, for placing the therapeutic medical devices and conduct the clinical studies being proposed. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| Aixa Bio | Kate Krueger | kate@aixa.bio | Founder and CEO | Cambridge, MA | Aixa is an innovative techbio company that uniquely combines genotypic and phenotypic data to identify early-stage medical leads. Its advanced approach, distinct from basic genome analysis, integrates patient symptoms with genomic data, enhancing diagnostic accuracy for a wide range of conditions with a genetic component. This positions Aixa as a leader in diagnostic and genomic tools, with significant potential in treating diseases like heart disease and metastatic cancers. | We're looking for clinical capabilities as well as computational biology teams. | TA1: Therapy recommendation techniques; |
| New York Stem Cell Foundation | Laura Andres-Martin | landresmartin@nyscf.org | raiyar@nyscf.org | New York, NY | Our work is focused on Women's reproductive cancers starting with ovarian cancer. Ovarian cancer remains one of the hardest cancers to treat due to a high degree of interpatient, intrapatient and intratumor heterogeneity. For most patients, the disease is diagnosed at an advanced stage with metastatic tumors that are still treated with one-size-fits-all kind of approach like chemotherapies. Our laboratories have established methodology to model, expand and preserve in a living biobank each patient’s tumor in the form of 3D tumor organoid cultures which have been shown to recapitulate patient’s treatment responses. Using these models we have also implemented fully automated drug testing methodology and immune cell killing assays to catalyze the clinical development process of emerging therapies and address the complex challenge of overcoming resistance. With this platform we aim to realize the potential of precision oncology and the discovery of novel effective treatment strategies for patients with ovarian cancer and other intractable women’s reproductive cancer types | We have established robust and reproducible fully automated mid-throughput patient-derived organoid-based drug testing technology that we would like to apply to identify biomarkers of sensitivity / resistance to treatments in longitudinal patient’s samples, samples from the same patient but distinct metastatic sites, or in recurrences resistant to therapy. We would also like to leverage our technology to model resistance ex vivo (induced or using organoids derived from samples exhibiting resistance) and apply molecular characterizations and functional assays via unbiased combinatorial drug testing to identify effective treatments | TA1: Therapy recommendation techniques;TA3: Treatment and analysis platform; |
| Brigham and Women's Hospital and Dana-Farber Cancer Institute | Kathleen Burns | kathleenh_burns@dfci.harvard.edu | Boston MA | We have discovered and are developing a novel blood-based cancer biomarker. Long INterspersed Element-1 (LINE-1) open reading frame 1 protein (ORF1p) is a transposable element protein overexpressed in carcinomas and high-risk precursors during carcinogenesis. We engineered ultrasensitive digital immunoassays that detect mid-attomolar (10−17 mol/L) ORF1p concentrations in as little as 25 μL plasma, allowing detection of multiple cancer types. See https://doi.org/10.1158/2159-8290.CD-23-0313 for more information. | We seek connections with ADAPT clinical trial teams who would like to incorporate LINE-1 ORF1p biomarker testing. | TA1: Therapy recommendation techniques; | |
| Icahn School of Medicine at Mount Sinai-Center for Advanced Research on Diagnostic Assays | Stuart Sealfon | stuart.sealfon@mssm.edu | alexandria.vornholt@mssm.edu | New York, NY | extensive track record in computational methods for multi-modal data integration, biomarker identification and predictive modeling, databasing, sample management, data generation | Coordinate with TA2 applicants for synergy | TA1: Therapy recommendation techniques; |
| Onai | Galana Gebisa | info@onai.com | San Jose, CA | Open state-of-the-art privacy-preserving technologies/platforms for oncologic and other healthcare data, including for data sharing, analytics, and AI -- our primary interest is TA3. We enable integrated use of different modalities of data across institutions. We also have deep expertise in biostatistical methods (such as for TA2). | Clinical partners | TA3: Treatment and analysis platform;TA2: Evolutionary clinical trial; | |
| John Snow Labs | Mwisa Chisunka | mwisa@johnsnowlabs.com | david@johnsnowlabs.com | Lewes, Delaware | John Snow Labs provides state-of-the-art software, models, and data to help healthcare and life science organizations put AI to good use. The team develops the open-source Spark NLP library (25,000 + models, 90+ million downloads, 250+ languages) and LangTest (100+ test types for Responsible AI), and commercially the Healthcare NLP library, Healthcare-GPT LLM, the NLP Lab No-Code Platform, and Medical Chatbot. The software is widely deployed across large pharmaceuticals, academic medical centers, government organizations, and health IT companies. One unique aspect of the software are oncology-specific and radiology-specific language models, which can extract 60+ facts like tumor staging, histology, biomarkers, and response to treatment from free-text pathology, radiology, and NGS reports. | John Snow Labs is looking to either lead or contribute to a team in TA3. We have deep experience and expertise in building large-scale, high-compliance, multidisciplinary data science platforms that enable teams to share data, models, and experiments. From designing to operating such a platform to managing an open-source community and encouraging adoption and collaboration, we’re happy to contribute to making this effort a successful service to the research community. We are also open to collaborating on TA1 or TA2. | TA1: Therapy recommendation techniques;TA3: Treatment and analysis platform;TA2: Evolutionary clinical trial; |
| Picture Health | Trishan Arul | trishan@picturehealth.com | carla@picturehealth.com | Cleveland, OH | Picture Health is a leader in the field of radiomics & pathomics – extracting AI-derived imaging feature biomarkers from radiology CT Scans & MRI’s, as well as pathology digitized H&E WSI’s. These imaging features tie to biological traits of the tumor and microenvironment (such as TIL infiltration or angiogenesis). We combine multiple features into unique “AI Signatures” to predict the likelihood of response to treatment and have demonstrated, in retrospective studies, that our features predict response across tumor types and treatments. We can also use Delta Radiomics, analysis of images over multiple timepoints, comparing features between the baseline pretreatment & follow up on-treatment CT Scans for early response detection prior to seeing gross changes in tumor size. Our Px Platform ingests images and other multimodal data and processes them through machine learning pipelines, to develop predictive signatures identifying responders vs non-responders prior to treatment initiation. We have created multiple signatures for NSCLC treated with IO and can create general signatures (high vs low risk patients) or specific signatures for a cancer & treatment combination. We have created effective predictive signatures for NSCLC patients receiving IO and also on novel agents with datasets of <100 patients (i.e. Phase 1 data). | We are looking for partners: with expertise in other modalities (spatial imaging, RNA seq, ctDNA, etc) to combine with our imaging features into multi-modal models for TA1 proposing for TA2 who would like to incorporate our imaging technology to measure & characterize the tumor as part of TA2.1 with access to cancer datasets including imaging for metastatic Breast & Colon cancer patients in order to produce proof of concept predictive imaging signatures for those cancer types relevant in TA2.2 (we already have metastatic lung cancer signatures) proposing for TA3 interested in incorporating our imaging pipeline technology to ingest, normalize, QC, annotate, and measure tumor characteristics We are currently planning to propose on our own for all or parts of TA1 and would like partners to join us in that. We are also interested in providing our technology & expertise to other prime proposers for any TA but are especially interested in joining other TA2 and/or TA3 proposals. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| Inova Schar Cancer Institute | Timothy Cannon | timothy.cannon@inova.org | petricoinpersonal@gmail.com | Fairfax, Virginia | We are proposing a prospective basket trial that uses proteomics to select molecularly targeted therapies. Our cancer instituate collaborates with our DOD funded proteomics core team, who are the leaders for the proteogenomic analysis of the APOLLO samples. We are completing our RPPA feasibility 100 patients trial, we have now set up a prospective targeted therapy trial with proteomic guided selection of targeted therapies. We currently have industry partners and philanthropic funding for a single institution basket trial that we call STUPP. Our hope is to use novel agents across the spectrum of targeted therapies and use both tissue based proteomics and plasma based proteomic results dynamically to assess for markers of response and resistance. | We would love to collaborate with interested partners, including but not limited to those with expertise in proteomics and data science. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| Focal Medical, Inc. | William A. Daunch | wdaunch@focalmedical.co | tvoiers@focalmedical.co | Cary, NC | Our novel technology is a first-in-class, technology platform that actively and precisely drives drugs into target organs using iontophoresis via non-circulatory pathways. Iontophoresis is the harnessing of mild electrical forces to transport molecules. With both implantable and non-implantable versions, we are developing targeted therapeutic products built on this active, energy-based targeting technology. Our research has broad application in the treatment of inoperable solid tumors and in the delivery of genomic medicines. Our lead program is a potential treatment for locally advanced non-resectable pancreatic cancer (clinical stage), complimented by a research pipeline program focusing on treating recurring oral cavity tumors (preclinical stage). We have successfully expanded our research portfolio beyond delivering small molecule oncologic drugs to include the local, extra-hepatic delivery of naked and encapsulated RNA medicines into solid organs, focusing on improving dosing, efficacy, and the elimination off-target effects. With experience in both pharma and medical devices, armed with a variety of in-vitro and in-vivo safety and efficacy evidence generation models developed for this platform, our team is uniquely positioned to develop novel targeted therapeutic products for the localized treatment of serious diseases. | Focal Medical, Inc. is looking for partners developing small molecule drugs or genomic medicines that may be interested in improving local delivery or are struggling with dose-limiting and/or off-target toxicities. In the cancer space, we are looking for partners with promising drug candidates that can benefit from high local dosing with minimal systemic spillover. In the genomic medicine space, we are looking for partners with promising drug candidates pursuing extra-hepatic delivery, seeking alternatives to complicated LNPs. | TA3: Treatment and analysis platform;TA1: Therapy recommendation techniques; |
| Anelia Horvath, George Washington University https://horvathlab.smhs.gwu.edu/ | Anelia Horvath | horvatha@gwu.edu | horvatha@gwu.edu | Washington DC | We specialize in detecting and analyzing mutations and variations using single-cell RNA and DNA sequencing data. Recently, we optimized a pipeline for analyzing cell-level expressed mutations and splicing isoforms from long RNA sequencing reads, including whole transcript analysis with technologies like 10x Genomics and PacBio. Our current focus is on developing accessible tools for identifying cellular-level mutations or variations, facilitating visualization and interactive exploration, and understanding their correlation with different cellular features. Our research has broad relevance across various cancer types. | We are interested in partnering with clinicians who are actively involved in administering therapies or conducting clinical trials, collect longitudinal blood or biopsy samples from cancer patients and have access to or utilize single-cell sequencing facilities or resources. We are also interested in collaborating with teams that investigate cancer response in vitro settings, and/or groups engaged in studying the efficacy of various therapies or interventions in preclinical cancer models. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| Zheng lab, Greehey Children's Research Institute | Siyuan Zheng | zhengs3@uthscsa.edu | AguilarV@uthscsa.edu | San Antonio, TX | My lab studies the cancer genome and computational biology. We aim to understand cancer evolution under various scenarios, including treatment, grafting, and ageing. We use and develop computational tools to dissect cancer evolutionary trajectories from bulk DNA, RNA sequencing data and single cell sequencing data. In the last few years, the lab has been working on (1) tumor evolution from patients to xenografts (PMID: 37990009); (2) how ageing shapes cancer genomes (PMID: 36433963); (3) algorithms to characterize telomeres and telomerase, for using them as markers during cancer evolution (PMID: 33420056; PMID: 28135248); (4) glioma evolution (PMID: 25650244). The lab also has substantial expertise in building web portals and databases (PMID: 32810235; PMID: 29099951). Our PCAT portal comprises molecular, clinical, and preclinical data of >200 childhood cancer PDX models. The portal has been part of NCI's CCDI effort. | We look for partners who have access to longitudinal tumor samples and who are interested in using genomic approaches to dissecting cancer evolution. My group has extensive experience in working with clinicians and bench scientists. | TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| Truveta | Margaret Wenzlau | margaretw@truveta.com | Seattle, WA | Truveta is a leader in EHR data and analytics, led by a growing health system collective that together provide more than 18% of all daily clinical care in the US. Truveta is trusted by more than 50 leading healthcare and life science customers to improve patient care, accelerate R&D, and inform public policy. Across these leading organizations, Truveta connects data, people, and ideas to pursue a shared mission of saving lives with data. | Truveta is looking to partner with organizations that can leverage Truveta Data - including, structured, unstructured, or imaging data - and platform capabilities in alignment with the ADAPT focus areas | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; | |
| OMAPIX Inc | Mridula Iyer | mridula.iyer@omapix.com | Nachiket Kashikar | stanford, CA | OMAPiX is on a mission to improve patient outcomes in precision oncology by leveraging best-in-class spatial multiomics technologies and data analytics. Spatial transcriptomics and proteomics provide critical data that allow us to have the deepest understanding of tumor microenvironment and heterogeneity. We are a team of industry-leading spatial omics experts, and probably the only company that has mastered end-to-end spatial omics data generation and analytics. We leverage leading technology platforms to generate high-quality spatial transcriptomics and proteomics data. This allows us to design complex programs for our partners for multi modal data analysis using our custom data analysis pipeline. Through our research, we enable new target discovery, complex intra- and inter-tumoral heterogeneity, investigation of immune tumor cross talk, and identification of new biomarkers. One of the major programs that we have undertaken is to analyze new spatial biomarkers for antibody-drug conjugate (ADC) therapy for advancing precision care in cancer aimed to improve patient outcomes. Our projects in Oncology are focused on developing novel standardized approach to integrate multi-modal data for downstream companion Dx characterized by unique spatial molecular signatures. | We look forward to partner with entities that we can team up for : (1) supporting multi modal spatial analysis, an expertise we offer on multiple technology platforms (2) supporting integrated data analysis using our custom data analysis pipeline (3) support for prospective clinical studies (4) identification of spatial signatures, differentially expressed markers to stratify patients leading to design of companion Dx panels for targeted therapy. Our program will enhance spatial resolution in samples of responders and non-responders to cancer therapy. Such collaborations will open new opportunities for discovering novel biological knowledge, biomarkers, and therapeutic targets. Our goal is to eventually develop a companion Dx to help identify crucial spatial information in patients. This will enable recruitment to trials more efficiently and effectively. We can eventually identify the right patients for treatment. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| Atrium Health Wake Forest Baptist Comprehensive Cancer Center | Wei Zhang, PhD, Professor and Director, Cancer Genomics and Precision Oncology | wezhang@wakehealth.edu | Jenny Kim (Comprehensive Cancer Center) <mjkim@wakehealth.edu> | Winston-Salem and Charlotte, North Carolina | Atrium Health Wake Forest Baptist Comprehensive Cancer Center (AHWFBCCC) is an integrated cancer center designated by NCI and serve cancer patients in the Carolinas and surrounding states with 2 Quaternary sites and 28 total care venues caring for over 20,000 new cancer patients in 2023. The AHWFBCCC is patient centric and research driven. Precision Oncology and Cancer Equity are two of the top priorities. Clinicians and scientists in our center are actively engaged in cancer genomics, cancer marker studies, and precision oncology in all target cancer types under ADAPT - lung, breast, and colorectal cancers. Our research strengths include our shared resources for omics including single cell sequencing, liquid biopsy, and microbiome. We have a strong bioinformatics teams with investigators who have been active in TCGA and AACR GENIE. | Whereas we are still in discussion internally regarding the specific cancer types our TA2 effort will focus, we welcome teaming with others in any of the three cancer types. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial; |
| Saltusbiotech | Andy Blidy | Saltusbiotech@gmail.com | ablidy@aol.com | Livermore California | SALTUS 8k Imaging system dramatically increases clarity and resolution of every biopsy slide for spatial biology . And the SALTUS 8k imaging system does something no other system in the world does – Microscopic MoviesTM of live biological tissue specimens. Patent pending When Pathologists see cells better with SALTUS Biotech 8K Imaging movie system: • Ease of use is better! • Accuracy is better • Precision is better! • Efficiency is better! • Analysis is better! • Viewing education slides is better! • Your Published data is better! • Cost savings is better! • Sharing digital data files is better and easy! Now, Saltus Biotechnology presents state of the art 8k Miroscopic Movies TM for Digital Pathology…..As we all know, Digital Pathology will become one of the most important medical technology in the next 10 years for your lab and of the entire healthcare system for both bright field and fluorescent monoclonal antibodies or probes. | Spatial Biology: This field of study focuses on understanding how the organization and localization of biomolecules within cells and tissues influences biological processes. stem cells like mesenchymal, dendritic, and monocytes/macrophages to become super APCs. These would be modified to express specific proteins like CTLA-4 and PD-1 (immune checkpoint proteins) to fine-tune the immune response against cancer. Advanced Imaging: Studying this process with high-resolution (8k) live-cell imaging would allow for a deeper understanding of how these engineered APCs interact with T cells and potentially improve the design of this strategy. High-Resolution Microscopy: Techniques like 8k Saltusbiotech resolution imaging could allow scientists to observe these interactions at an unprecedented level of detail. | TA1: Therapy recommendation techniques;TA3: Treatment and analysis platform; |
| Maitra Lab at MD Anderson Cancer Center | Anirban Maitra | AMaitra@mdanderson.org | PAGuerrero@mdanderson.org | Houston, Texas | Our laboratory has developed a pipeline for isolation, next generation sequencing and computational deconvolution of extracellular vesicular RNA (evRNA) cargo from the plasma of healthy individuals and from patients with cancer. This optimized liquid biopsy pipeline allows us to longitudinally profile the transcriptomic subtypes of cancers at baseline and in the course of treatment with targeted therapies and immunotherapy (Bahrambeigi et al, Cancer Res 2024). Our pipeline allows interrogation of adaptive cancer-related pathways that emerge in the context of treatment resistance and tumor evolution, sans the need for repeated tissue biopsies. Further, our pipeline can be used for tracking cancer-related fusion events and for identifying expressed neoantigen related transcripts in blood. In the foundational study, we have also shown the utility of our platform for monitoring patients with minimal residual disease (MRD). We have deployed our evRNA platform in clinical trials of patients with metastatic cancer receiving small molecule KRAS inhibitors and identified oncogenic pathways and specific molecular events that drive resistance to these therapies (unpublished data). The biospecimen requirements for evRNA profiling can be readily incorporated within standard clinical draws. | We are open to partnering with clinical trial partners that can leverage our longitudinal evRNA pipeline for application in evolutionary clinical trials (TA2) in order to determine adaptive resistance pathways (both unbiased and targeted), as well as for novel biomarker discovery and validation studies (TA1). The pipeline we have developed has been tested in the context of colorectal and pancreatic cancers, but is amenable for deployment in any solid cancer type. | TA2: Evolutionary clinical trial;TA1: Therapy recommendation techniques; |
| Beckman Research Institute, City of Hope | Russell Rockne | rrockne@coh.org | maramirez@coh.org | Duarte, California | Mathematical modeling of longitudinal data, blood transcriptome, and biomarker discovery. | Access to clinical samples and software pipeline development expertise. | TA1: Therapy recommendation techniques; |
| American College of Radiology | Charlie Apgar | capgar@acr.org | akerns@acr.org | Reston, VA | ACR supports research through 3 entities: Center for Research and Innovation (CRI) which focuses on clinical research, Neiman Health Policy Institute (NHPI) which focuses on health policy, and Data Science Institute (DSI) which focuses on AI and informatics. The CRI has conducted ground-breaking clinical trials in healthcare screening and novel imaging methodology, leading to FDA approvals of imaging devices, software and therapeutics. The CRI is a leader in RWD/RWE with specific expertise in cancer and Alzheimer’s disease and is one of the first innovators to use the Coverage with Evidence Development process under CMS. The NHPI is the leading authority on radiology health policy research with access to extensive medical claims datasets: Medicare, Medicaid, and private payers. Peer reviewed findings are cited in support of national health economic decisions and are instrumental in determining cost-effective care delivery models. The DSI was launched to promote the safe and effective use of AI in medical imaging. They have created a collaborative environment for industry, government, and stakeholders to focus on issues required for AI to thrive in practice. The DSI is engaged with the FDA to help create guidance for AI development in real-world settings and ongoing monitoring. | The ACR aims to work with others in the way we have always excelled in research and radiology—by working collaboratively. The ACdR brings together disparate perspectives to solve problems. We convene images, data, and ideas an are responsive and reliable research partners. Potential collaborators could leverage ACR’s expertise and various programs to collaborate and drive the science forward, resulting in improved patient outcomes. Radiology and imaging are essential in almost all aspects of early detection, diagnosis, and treatment of various diseases, and the expertise ACR brings would be well suited for the ADAPT program. The ACR has developed a robust infrastructure with core strengths in informatics and data and research. By collaborating with scientists and clinicians in the field, innovative ideas have led to research findings which have informed the development of evidence-based practice guidelines, created decision support tools, provided education, and developed the other quality measures that are needed to adopt change and improve practice. We would envision extending this collaborative approach to include organizations, clinicians and industry in a structured environment where we can contribute our expertise to the development of research projects that enable real-world testing of new innovations. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| Leapfrog Bio | Tomas Babak | tomas@leapfrog.bio | doris@leapfrog.bio | San Mateo, CA | Leapfrog Bio is a venture-backed precision oncology company focusing on developing genetically targeted therapies. Leapfrog uses a clinically-validated pharmacogenomic platform to identify synthetical lethal relationships between common loss of function driver perturbations and small molecule drugs. By accurately generating cancer-causing events in native contexts and by capturing the full pharmacologic effects of a drug on cell biology, the platform outputs faithfully predict targeted opportunities with overall survival benefits. This predictive ability greatly increases the probability of success of Leapfrog’s programs as compared to standard de novo drug development approaches. The company is focused on screening shelved clinical-stage drugs where safety has been derisked, and reintroducing them as genetically targeted therapies into patients with the Leapfrog-identified sensitizing mutations, where efficacy is highly probably. The company is currently initiating Phase 2 clinical development of its two first-in-class assets. | Looking for one or more of the following: 1) access to and experience in integrating RWD with tumor mutations and drug treatment history (e.g. PFS is higher in patients with mutation X treated with drug Y), 2) drug screening in cell lines and access to diverse compound libraries, and/or technlogies for enabling automation 3) execution of genetically targeted clinical trials in solid tumors | TA1: Therapy recommendation techniques; |
| Biosortia, Inc. | Ross Youngs | ryoungs@biosortia.com | chummell@biosortia.com | Dublin, OH | Biosortia's pioneering technology marks a significant shift in microbiome research and drug discovery. Traditional methods have only scratched the surface of microbiomes, leaving vast potentials of small molecules and enzymes hidden within these complex microbial communities unexplored. Biosortia's approach, however, revolutionizes this field through industrial-scale microbiome mining, providing direct access to these elusive molecules and enabling significant advancements. This technology accelerates our understanding of microbiomes and serves as a powerful tool for drug discovery, potentially addressing global health challenges. Its integration with indirect omics, AI, and other modern techniques enhances existing research capabilities, promising faster discovery of novel bioactive compounds. Biosortia's innovative solution signifies the dawn of a new era in scientific discovery, where the mysteries of microbiomes could offer groundbreaking solutions in healthcare and medicine. Our goal is to obtain and use these hidden molecules from natural microbiomes to accelerate the discovery of starting points for therapeutics and fingerprinting of the sub-peak molecules in the human body precision medicine. | Biosortia Pharmaceuticals proposes to collaborate with the ARPA-H ADAPT program by leveraging our pioneering technology in industrial-scale microbiome mining to uncover novel cancer-fighting small molecules and enzymes. Our unique approach allows us to access and analyze previously hidden compounds within microbiomes, offering a treasure trove of potential cancer therapeutics and biomarkers. This capability aligns perfectly with ADAPT’s objectives, particularly in addressing the challenge of therapy-resistant cancers through the development of innovative biomarkers and therapeutic agents. Our technology enhances ADAPT’s focus on therapy recommendation techniques by providing a rich, untapped source of data for multi-modal fusion and resistant trait modeling. By integrating our findings with ADAPT’s evolving database and algorithms, we aim to broaden the repertoire of actionable biomarkers, facilitating the prediction of drug responses and resistance patterns. Furthermore, our contribution could be instrumental in the evolutionary clinical trial envisioned in technical area 2, offering new avenues for identifying emergent resistant traits and therapy biomarkers. Through this collaboration, Biosortia aims to accelerate the discovery and implementation of adaptive, personalized cancer treatments, ultimately improving outcomes for patients with metastatic cancers. Together, we can create a dynamic ecosystem of data, research, and innovation, driving forward the frontiers of cancer care. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial; |
| Department of Biomedical and Pharmaceutical Sciences, Idaho State University | Ali A. Habashi | habaali@isu.edu | aliaghazadehhabas@isu.edu | Pocatello, Idaho | The Department of Biomedical and Pharmaceutical Sciences (BPSCI) focuses on biomedical research and pharmaceutical science, specifically drug discovery and development, novel peptide drug delivery, pharmacokinetics/pharmacodynamics, biomarkers, neurosciences, etc. | Looking for teaming partners specialized on cancer biology and have access to cancer patients biospecimen for studying biomarkers of cancer. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial; |
| Sostos LLC | Nancy Guo | nancyguo@sostosllc.com | danflynn@sostosllc.com | Morgantown, WV | Sostos has developed a unique software technology that can identify personalized cancer treatment solutions for patients. Our Artificial Intelligence (AI) system is called CATOS - Cancer Treatment Optimization Solution. CATOS can scan large genomic datasets and predict the optimal approach for cancer screening, diagnosis, prognosis, and treatment. CATOS allows for a customized approach for an individual’s cancer, and the development of novel diagnostic assays for patients. The CATOS system has been proven to be effective and accurate for precision diagnostics, with 62 published scientific articles and more than 3,926 citations. The initial CATOS product, a 7-gene lung cancer assay (CATOS-LU), has been validated in 1,641 patients including a randomized phase III clinical trial. The FDA has classified CATOS-LU as a “Novel Technology” (under review). The CATOS software platform has over 46,000 browses, which will be upgraded for premium paid use. In addition, CATOS can be used for drug discovery, by identification of new cancer treatment options from drugs that are currently approved for use for other diseases, which can be safely repurposed for cancer treatment. Using our software, we have discovered and filed patents for 8 diagnostic assays and 21 ‘repurposed’ compounds. | Sostos seeks partners that generate genome-scale measurements of multi-omics profiles in patient liquid biopsies, bulk tumors, and single cells. With Sostos' cutting-edge AI software technology for analyzing multi-omics data for biomarker discovery and drug development, this partnership can create synergy to advance personalized cancer therapy. | TA1: Therapy recommendation techniques;TA3: Treatment and analysis platform; |
| LighTopTech Corp. | Cristina Canavesi, PhD, MBA | cristina@lightoptech.com | West Henrietta, NY | LighTopTech builds innovative optical instruments to bring to market disruptive technologies for noninvasive imaging on multiple scales. Combining wide-field of view imaging and three-dimensional sub-cellular imaging with machine learning methods, we achieve rapid screening and unbiased, automated whole organoid / tumor spheroid characterization. | We are interested in partnering with teams that are looking for noninvasive, wide-field (10 mm x 10 mm single shot) rapid 3D screening and imaging of whole organoids with micron-level resolution | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; | |
| Nexogen, Inc. | Dalibor Hodko | dhodko@nexogentech.com | San Diego, CA | Nexogen, Inc. has developed a disruptive point-of-care diagnostics platform that enables rapid multiple nucleic acid and protein-assays to be performed simultaneously on the same disposable cartridge. The sample-to-answer time for multiplexed direct identification of DNA, RNA, or protein targets (up to 200-500 biomarkers) is within 15-20 minutes. This platform brings for the first time both biomarker identification and host-response detection e.g., based on epigenetic methods (mRNA expression, ATAC assay, methylation, CUT&Tag methods, etc) as well as embedded multiomics algorithms to differentiate biomarkers on the same disposable cartridge. The platform is envisioned to be used as a rapid adaptive tool for monitoring cancer (or infectious disease) clinical studies, or monitoring therapy by implementing biomarkers individualized for a particular patient. Our innovations enable 2-3 min isothermal amplifications of both nucleic acid and immuno-targets, a generic, up to 100-fold acceleration of molecular biology reactions, the array sensors at a cost of ~$1 per 100 targets/spots and a new microfluidics system that enables accurate transfer of reference lab methods to a disposable cartridge. The platform is adaptable to rapid liquid biopsy, ~ 30 min sample-to-answer by monitoring both DNA and protein biomarkers (e.g., CancerSeek type assays where ~60 DNA and ~10 protein biomarkers could monitor 9 type of cancers). | Nexogen is looking to collaborate with teams with cancer drug development focus as well as with teams involved in modeling algorithms that identify cancer biomarkers, in particular those capable of individual patient’s response to therapies. We envision a close collaboration with these teams that will lead clinical studies using new or multiplexed biomarkers important in drug development or monitoring therapy, or therapies applied on individual patient’s basis. Nexogen will closely collaborate to develop assays on our platform with multiplexed cancer biomarkers developed by those teams, and based on DNA, mRNA, protein analytes. Focused biomarkers for monitoring a particular cancer, therapy, e.g., by liquid biopsy, with multiplexing capability up to 500-1,000 analytes. Since our platform is extremely rapid, enabled by electric/magnetic field acceleration of biomolecular reactions, where the most complex assays can be performed within ~25 min. We envisioned that this platform will enable rapid, focused and low-cost monitoring of advancements of your clinical cancer studies or monitoring individualized response of cancer patients to therapy. Our method promises that highly complex multiplexed cancer analysis could be implemented at a point-of-care. | TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; | |
| Netrias, LLC | Mark Weston | weston@netrias.com | pboutet@netrias.com | Annapolis, MD | Strong capabilities in TA1.1: Multi-Modal Data Fusion, including automated harmonization and curation techniques, data structure parsing and semantic mapping, and multi-dimensional embeddings. | We are looking for teaming partners that can support efforts in TA1.2: Resistant Trait Modeling as well as TA1.3: Biomarkers that Predict Drug Response. We are open to discussing teaming arrangements depending on overall strength and capabilities of the teaming, including Prime or Subcontracting. | TA1: Therapy recommendation techniques; |
| ExThera Medical Corporation | Keith McCrea | keith.mccrea@extheramedical.com | annette@extheramedical.com | Martinez, California | ExThera Medical Corporation has developed the Seraph® 100 Microbind® Affinity Blood Filter (Seraph 100), a well-tolerated, extracorporeal blood filter containing millions of polymer beads surface modified with heparin to mimic the glycocalyx of mammalian cells. Seraph 100 has been used successfully in the treatment of COVID 19 and other viremias, bacteremia, fungemia, and most recently, in a first-in-human cancer trial. It is an extracorporeal blood filter (EBF) capable of quickly reducing circulating tumor cells and cancer stem cells to undetectable levels, even at modest blood flow rates. It can simultaneously treat metastatic cancer and the pathogenemias that often afflict cancer patients. Seraph 100 EBF has potential in several area: 1) Slowing metastatic disease progression by rapid adsorptive CTC removal, 2) Immunomodulatory effects from debulking the blood of both CTCs, pathogens and acellular ‘debris’, thereby enabling immune system reactivation, and 3) Diagnostic and personalized treatment of the cancer using cells captured by the filter and optionally cultured. Seraph 100 interrogates the patient’s entire blood volume as it concentrates the cellular and acellular adsorbates that it removes for analysis. It is therefore an Intelligent Therapy ideally suited to personalized treatment of cancer and pathogenemia, in combination with existing therapies. | ExThera seeks to team-up with research organizations capable of enumerating and analyzing CTCs, cancer stem cells, exosomes and miscellaneous ‘debris’ removed from a patient's blood by our Seraph 100 Extracorporeal Blood Filter. As the Seraph 100 can capture up to 99 % of circulating tumor cells (CTCs) and cancer stem cells (CSCs) per pass, it can ‘interrogate’ a patient's entire blood volume very quickly during an optionally combined therapeutic/diagnostic procedure. We anticipate supplying our partners with a substantial quantity of tumor-derived components, which will be invaluable for identifying emerging resistance traits and therapeutic biomarkers. | TA2: Evolutionary clinical trial; |
| Lunit | Ken Nesmith | ken.nesmith@lunit.io | siraj@lunit.io | Cambridge, MA | Lunit builds multimodal AI image analysis for early cancer detection, and for post-diagnosis cancer treatment planning. Lunit's radiology AI analysis includes x-rays, mammograms, DBT, CT, and more. Lunit's digital pathology AI analysis includes H&E, IHC, spatial genomic and proteomic technologies, and multiplex analysis. | Lunit has deep experience in radiology AI for early cancer detection, and digital pathology AI for cancer treatment planning. Example teaming partners could include health systems looking to integrate multimodal data in new ways for cancer diagnosis and treatment response prediction, hardware companies (e.g. imaging, digital pathology, etc) looking to advance the frontier of capabilities in partnership with an AI-focused company like Lunit, or clinical research organizations looking to more deeply integrate AI into patient identification and enrollment, and biomarker development and use within trials. | TA1: Therapy recommendation techniques;TA3: Treatment and analysis platform; |
| University of California, San Francisco | Jim Wells | jim.wells@ucsf.edu | kevin.leung@ucsf.edu | San Francisco, CA | We are keenly interested in how cells remodel their surfaceome in health and disease, and to develop novel antibody-based therapeutics that target them. For the last decade, we have been studying how the surfaceome of cancer changes in context of oncogenesis, metastasis, and drug resistant using state-of-the-art proteomics techniques. In particular, we are interested in assessing surfaceome protein abundance, PTMs, protein conformation, and interactome that are unique to cancer as a means of targeting them. Using antibody-phage display technology, we endeavor to develop antibodies against the cell surfaceome. For highly specific proteoforms, we have also developed selective binders that target these specific protein states. | We are looking for teaming partners who would provide patient samples or serum samples for detection of novel biomarkers using state-of-the-art proteomics techniques. We are also looking for highly selective proteoforms of interest that may be amendable to antibody development campaigns. | TA1: Therapy recommendation techniques; |
| Legorreta Cancer Center at Brown University (LCC-BU) | Wafik S. El-Deiry, MD, PhD, FACP, Director | wafik@brown.edu | catherine.bresson@winconsortium.org | Providence, Rhode Island | Legorreta Cancer Center at Brown University (LCC-BU) has substantial resources for discovery and development of molecularly-targeted novel therapeutics as a high priority. LCC-BU’s director El-Deiry (MD, PhD, FACP) focuses on laboratory-based translational clinical protocols in drug resistance and biomarker-driven cancer therapeutics. El-Deiry discovered CDK inhibitor p21(WAF1), DR5 and TRAIL/innate immune/integrated stress response stimulator ONC201/TIC10 currently in phase III trials for H3K27M-mutated diffuse midline gliomas. El-Deiry brings capabilities of non-profit Worldwide Innovative Networking (WIN) Consortium in precision oncology (PO) that he's chaired since Dec. 2023 (LCC-BU is a WIN member). WIN is growing in US and globally. WIN PO trials enrolled patients globally and led the field in demonstrating clinical benefit through innovative transcriptomics, algorithms and Molecular Tumor Board interventions for patients with advanced cancer across tumor types. World Iterative Next Gen Precision Oncology (WINGPO) is a Next-Gen PO N-of-1 980-evaluable patient study to prolong survival of patients with advanced cancer using advanced technologies, algorithms and iterative designs. The vision and plans of the WIN Consortium have been recently described in The Cancer Letter, Issue 45, Volume 49, December 8, 2023 and HemOnc Today Byrne, J. (2024, January 22), WIN Consortium chair aims to promote collaboration, innovation in personalized medicine, Healio. | We would like to expand the portfolio of drugs that can be made available to patients beyond on-label use and compassionate off-label use. Inclusion of pharmaceutical partners willing to make drugs available (approved and investigational) would propel the field forward. We are communicating with drug companies, cooperative groups and professional associations but a public solicitation for pharmaceutical partners is in order to complement our existing strategies. We are keen to collaborate with those developing technology platforms that can use blood, tissue including organoids and who may have algorithms that could add value to the program while being tested on patient outcomes. | TA2: Evolutionary clinical trial;TA1: Therapy recommendation techniques; |
| Boston University Medical Campus | Gerald Denis | gdenis@bu.edu | ospera@bu.edu | Boston, Massachusetts | We have discovered that plasma exosomes carry miRNA profiles that vary greatly as a function of patient metabolic status, and which are functional, capable in diabetes of driving increased tumor aggressiveness in breast and prostate cancer, and likely other solid tumor types. Unlike approaches that identify circulating exosomes of tumor-origin, we investigate adipocyte-origin exosomes that are altered in patients with obesity and diabetes and drive metastasis and drug resistance. We also have identified a biomarker of telomere length and stability, assayed by IHC or IF, that strongly associates with outcomes and mortality in prostate, lung and breast cancer. These two biomarkers may be valuable when combined with radiological, serological and tissue-based measurements of treatment response for a wide array of solid tumors, particularly obesity-associated cancers. The patient populations most likely to benefit from these innovations are treated at safety net hospitals where the prevalence of obesity and diabetes is high, and who are not well served by the standard of care, which has tended to exclude from clinical trials patients with any cardiometabolic history. | We are interested to partner with clinical trial sites where solid tumors are treated with targeted agents, immune checkpoint inhibitors and other modalities in the standard of care, particularly where comorbid metabolic disease is prevalent among patients. Our preliminary data support a role for both telomere biomarkers and plasma exosome biomarkers as predictors of response and outcomes for breast, prostate and liver cancers, although we are interested in other prevalent solid tumors as well. We have a CLIA certified facility capable of handling tissue, (e.g. FFPE) and plasma for high throughput analysis of these biomarkers to determine association with treatment response. Preliminary data support the utility of these biomarkers for breast and prostate cancer, and hepatocellular carcinoma. We are interested to determine utility for renal, colorectal, endometrial and other solid tumors. | TA1: Therapy recommendation techniques; |
| CureMatch, Inc. | Gilles Godard | ggodard@curematch.com | aperlina@curematch.com | San Diego, CA | CureMatch, molecularly matches, scores, and ranks drugs and drug combinations (including novel combinations of FDA-approved drugs) to patients' cancer profiles (NGS of somatic DNA, RNA, protein data). CureMatch Oncology Report also identifies any drugs or combination therapies that may be potentially harmful due to unique molecular biomarkers in some patient’s profiles suggestive of resistance or hyper-progression risks. This service helps physicians make faster more molecularly informed therapy selection decisions and has been granted a CPT code by the AMA. The governing precision matching approach has demonstrated in clinical studies that higher molecularly matched cancer therapies are correlated with better clinical outcomes for both, time to progression and overall survival across cancers. Poorly matched therapies are associated with worse disease progression and overall survival outcomes in cancer patients. The same technology and underlying knowledge base for therapy scoring is also applicable for investigational compound(s) of choice to optimize biopharma clinical trials and improve chances of success. CureMatch Clinical Trial Intelligence solution can aide patient stratification and clinical trial design to increase efficacy, reduce chances of adverse effects, dropouts, and failure. Real World Data from past trials can also be used to inform new trial design or trial rescue options. | We are interested in working with oncologists who are actively involved in treatment decisions or conducting clinical trials where cancer patients NGS profiling results are expected or already available for tissue or liquid biopsy samples. We use such results along with any other CLIA-grade molecular lab reports as inputs to generate a CureMatch Oncology Report, which qualifies and quantifies custom drug combinations, as well as known available cancer therapies on the basis on a patient’s cancer molecular profile. The report also helps warn of potentially harmful drugs or combinations for individual molecular reasons. As a result, we can help the care team or tumor boards consider the most molecularly informed treatment options. We are also interested in working with pharmaceutical companies as part of CureMatch Clinical Trial Intelligence (CTI) to assess the molecular matching of the trial therapy to the clinical cohort based on NGS data and mechanism of action of the drug(s), which can help derisk and optimize clinical trials. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| CartaBio | Rob Yang | rob@cartabio.ai | Belmont, MA | single-cell spatial omics + multi-modal foundation model | Looking for partners with expertise in clinical imaging, EMR, histology. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial; | |
| Ohio State University James Cancer Center | David Carbone | david.carbone@osumc.edu | katherine.hughes@osumc.edu | Columbus, OH | Precision molecular analysis of lung cancer biology, drivers, mechanisms of resistance to immunotherapy and targeted therapies, and mechanisms of persistence. | Whatever is synergistic | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| AACR Project GENIE | Tony Wu | tony.wu@aacr.org | shawn.sweeney@aacr.org | Philadelphia, PA | AACR Project GENIE (GENIE) serves as an open and pivotal international cancer registry, stemming from a collaborative effort among leading international cancer centers. GENIE champions open science, aggregating and making available both historical and ongoing clinical-grade sequencing data from more than 180,000 patients with 210,000 samples. Clinical, demographic, and outcomes data, linked to the appropriate patient IDs, provide the genomic-outcomes relationships necessary to help academic, biopharmaceutical, regulatory, and the larger oncology research community develop new therapies, design better clinical trials, and personalize treatment to ultimately make improved clinical decisions. Our key research areas include: 1. Data Quality and Standards: Implementing rigorous quality control and assurance processes to ensure the integrity and quality of genomic and clinical data. 2. Infrastructure Evolution: Developing a flexible, scalable infrastructure that can adapt to emerging data types and technologies in oncology research. 3. Collaborative Governance: Operating under a consortium model, GENIE champions open data sharing to promote collaborative public-private research efforts. 4. Operational Excellence: Maintaining centralized oversight of data collection, harmonization, and analysis to uphold the highest standards of data production and delivery. 5. Regulatory Strategy Support: Utilizing real-world data to facilitate industry clinical development, regulatory submissions, and post-marketing surveillance, aligning with global regulatory standards. | GENIE collaborates with potential partners through a model of open data sharing and joint research initiatives. Partnerships are formed with leading cancer centers, industry diagnostic and drug developers, and regulating body stakeholders in the biopharmaceutical and payer sectors. GENIE facilitates these collaborations by providing access to its comprehensive database of clinical-grade genomic and clinical data, enabling partners to conduct advanced oncology research and development projects. The collaboration process involves establishing agreements that respect data privacy and intellectual property while ensuring the mutual benefit of all parties involved. GENIE and its partners engage in joint studies, leveraging the extensive data resources to explore multi-modal advances in cancer research, drug development, and precision medicine strategies. By working together, GENIE and its partners enhance clinical trial designs, accelerate drug development processes, and contribute to more effective and personalized cancer treatments. GENIE addresses health disparities with an intentional effort to improve outcomes for all patient populations. Through these collaborative efforts, GENIE strengthens its mission to improve clinical-decision making through open science | TA3: Treatment and analysis platform;TA2: Evolutionary clinical trial;TA1: Therapy recommendation techniques; |
| Schiffer lab - UMass Chan Medical School | Celia Schiffer | Celia.Schiffer@umassmed.edu | Nese.KurtYilmaz@umassmed.edu | Worcester, MA | The Schiffer laboratory has 25 years of experience (and over 200 publications) investigating the molecular basis for drug resistance using a combination of structural biology and computational chemistry. We can accurately predict the potential of resistance to a drug by target mutations based on structural analysis of molecular interactions and the target’s functional constraints by evolution. We can predict which inhibitor/therapy option would work best for a given resistant variant and which mutations might evolve for a given drug. Our methods are applicable to both small molecule and biologics (protein/antibody)-based therapeutics. www.umassmed.edu/schifferlab | We are interested in contributing to teams in identifying mutations in a drug target that confer resistance, from a mechanistic and structural perspective. We bring in both structural biology expertise as well as advanced computational approaches to identify likelihood potential of drug resistance for any therapeutic – target pair. | TA1: Therapy recommendation techniques; |
| HealthX_Open | Nilar Myint | Nmyint@healthxopen.org | nmyint2019@gmail.com | New York | Justifiable and simplified health System, focus on cooperation, less fragmentation, interconnected patient centered healthcare delivery | Improving quality of health and quality of life | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| BevelCloud | Timothy Chou | tim@bevelcloud.io | julee@bevelcloud.io | Marina del Rey, California | A scalable distributed data management platform that harmonizes and annotates disparate multi-modal data from cancer researchers and clinical trials nationwide – at the source. The platform provides a flexible, collaborative computational pipeline to rapidly and securely process tumor biology measurements, perform QC analysis, manage data curation, annotate and link disparate data types from the patient, while preserving privacy. The platform provides open APIs, a data portal, and tools for multi-modal access, analysis, sharing, querying and visualization. | Cancer researchers or clinicians who are interested in using multi-model data from next-generation sequencers (NGS,) RNA sequencers, Sanger sequencers, Single-molecule sequencers, microarrays, Nuclear magnetic resonance (NMR) spectrometers, Mass spectrometers, Multiplex immunofluorescence imaging systems, Spatial transcriptomic equipment, Multiplexed ion beam imaging (MIBI) machines, Spatial proteomics imaging systems, Spatial genomic machines and ultrasound, CT, MRI, Xray, Microscope, Blood Analyzer, ECG/EKG Bedside Monitor | TA3: Treatment and analysis platform; |
| Isabl Inc. | Elli Papaemmanuil | elli@isabl.io | juan@isabl.io | NYC, NY | Isabl Inc. improves cancer diagnosis, prognosis, and biomarker discovery with cancer whole genome and transcriptome (cWGTS) sequencing assays and analytics. Isabl’s technology was developed and validated at Memorial Sloan Kettering Cancer Center, (Shukla, et al Nat Communications 2022) demonstrating comparable sensitivity to FDA-approved panel assays, rapid sample-to-report solution (9 days), and characterization of genetic findings of clinical relevance that can only be detected by cWGTS such as complex structural variants. Isabl has developed laboratory protocols for the generation of clinical grade cWGTS data from solid tumors, including fresh frozen and FFPE biospecimens, as well as diagnostic cfDNA for patients with relapsed or metastatic disease. Isabl’s workflow delivers rapid, fully automated analyses and biomarker annotations across the wholegenome, enabling precise diagnosis and personalized treatment strategies for cancer patients. Results are aggregated into Isabl’s web portal, which supports physician friendly biomarker queries across all data modalities (germline, tumor DNA, tumor transcriptome), classes of somatic mutations inclusive of small gene mutations, detailed copy number analysis, structural variants, and clinically relevant mutation signatures (e.g., Homologous Recombination Deficiency). The FDA has granted Isabl's technology Breakthrough Device Designation and Isabl is currently funded by the NCI (SBIR) to clinically validate Isabl GxT as an LDT in 2025 Q1. | Isabl is uniquely positioned to support biomarker development efforts for ADAPT. The premise of ADAPT is focused on how we can adopt cancer treatments as tumors mutate and change? Wholegenome sequencing (WGS) is the only assay that can deliver a complete view of all mutations in a patient's tumor using a single assay. Integration of WGS findings to other data modalities and outcomes can accelerate biomarker development studies. Isabl GxT, is a clinical grade cancer WGS and transcriptome sequencing assay. Isabl’s advanced WGS analytics enables extraction of all molecular biomarker signals from a single assay within 24 hours from data generation. Isabl GxT is uniquely powered to be the tumor measurement assay of choice for TA2.1. Isabl Platform is a digital biobank that integrates multi-modal patient data (e.g., genomic, transcriptomic, imaging) in a compute-ready environment, facilitating the automatic deployment of complex analytical workflows at scale. As a patient-centric data architecture, Isabl Platform can readily link serial sampling data to clinical metadata for a given patient to map a patient's tumor evolution. The platform can directly support TA1 (data fusion) and TA3 initiatives. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| Verily | David Glazer | dglazer@verily.com | seanhorgan@verily.com | South San Francisco, California | Our purpose at Verily is to bring the promise of precision health to everyone, every day. We deliver new data, evidence, and software solutions that accelerate clinical research and enable more personalized care for a bridge to a healthier future. Precision health starts with precision data. Our precision health platform is a comprehensive patient-centered engine that accelerates the evidence generation needed for safer, more effective treatments and care decisions. We use scalable ingestion and harmonization techniques to bring multiple datasets together on a single platform, and make data useful through customizable enrichment and analysis tools. Verily Workbench is a secure research environment for governing and analyzing global multimodal biomedical data. We aspire to transform biomedical research by making the world’s most scientifically valuable data discoverable, accessible, and analyzable, all while respecting regulatory and ethical policies. To realize that vision, we support the end-to-end lifecycle of data that is governed, research that is reproducible, and collaboration that is easy and secure. Our cloud-based platform includes an extensible library of ingestion pipelines, exploration tools, data visualizations, and analysis methods. Researchers and partners can use open standards to add new domain- and project-specific tools, both open source and proprietary. | We are looking for collaborators to work with us on building and operating ADAPT-specific methods and tools on our precision health platform. We bring deep scalable technical and infrastructure capabilities, and experience putting that to work in multiple data modalities (multi-omic, clinical, imaging, sensors, self-reported) across multiple medical conditions, research areas, and study designs. We would like to complement our team with expertise in the specific new and existing data modalities that will be generated in ADAPT, and experience putting data to work in discovering biomarkers and tailoring study protocols and care pathways in metastatic cancers. | TA3: Treatment and analysis platform; |
| Medical University of South Carolina | Besim Ogretmen | ogretmen@musc.edu | piercej@musc.edu | Charleston, SC | The mission of the Lipidomics Shared Resource (LSR) is to provide state-of-the-art instrumentation and cost-effective resources to study lipid metabolism and signaling to the scientific community. The scientific goal of the LSR is to help identify bioactive lipids as biomarkers to monitor therapeutic responses in patients and examine their roles in tumor cell biology to discover and evaluate drugs that target lipid metabolic processes. The LSR is the only NCI cancer center-affiliated lipidomics facility with combined analytical, synthetic, and imaging capabilities. This is enabled by state-of-the-art technology including Thermo TSQ-50003, SCIEX Q-Trap triple quadrupole/ion trap, Advion TriVersa Nanomat, Bruker Faltonics AutoFlex III linear MALDI, and AutoFLexIII MALDI TOF-TOF. The LSR has integrated matrix assisted laser desorption/ionization (MALDI) imaging capability for direct tissue analysis of sphingolipid and glycolipid species in tissues, drug distribution in tumor xenograft tissue and organs (brain, kidney, liver), and structure confirmation of drug or metabolites of interest by collision-induced fragmentation. Thus, by combining mass spectrometry and MALDI imaging, this resource not only quantifies sphingolipids, glycolipids, free fatty acids, and prostaglandins in tumor tissues and in single cell resolution but also provides information about their cellular location and distribution. | The Lipidomics Shared Resource (LSR) is one of the few lipidomics facilities in the US. It has built a worldwide reputation and customer base and is the only cancer center-affiliated lipidomics facility with combined analytical, synthetic, and imaging capabilities, designed to provide cost-effective access to cancer researchers for their studies of lipid metabolism and signaling in cancer. This shared resource has demonstrated an exceptional abil-ity to serve growing numbers of researchers and investigators at many leading national and international re-search centers, supporting impactful discoveries, top-tier publications, programmatic grants, and clinical studies using universally accepted and validated mass spectrometry-based lipidomics methodologies. The scientific goal of the LSR is to help identify bioactive lipids and their role in tumor cell biology and discover and evaluate drugs that target lipid metabolic processes in clinical trials. We are seeking to foster scientific partnerships to discover novel lipid-based serum biomarkers for monitoring therapeutic responses in cancer patients. Also, the LSR has integrated MALDI imaging capability for direct tissue analysis of sphingolipid and glycolipid species in tissues, drug distribution in tumor xenograft tissue and organs (brain, kidney, liver), and structure confirmation of drug or metabolites of interest by collision-induced fragmentation. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial; |
| UCSF | Jeroen Roose | jeroen.roose@ucsf.edu | nicole.yee@ucsf.edu | San Francisco, CA | Cell-cell interaction. The Roose lab at UCSF studies mechanisms of cell-cell interactions in immunology and cancer, with emphasis on personalized medicine, and single cell approaches to deconstruct diseases. Organoids. Through our work on cancer & stem cells, the Roose lab established organoid protocols. We successfully generate organoids from UCSF patient samples and build Living Biobanks. Using this patient organoid biobank as foundation we execute fundamental research projects with focus on cancer metastasis and cancer cell-host cell interactions. We also capitalize on these organoid mini-patient avatars to test efficacy of existing cancer therapies and explore new therapies. | We are interested in being integrated in a team that can capitalize on our expertise to investigate cell-cell interactions with single cell approaches and our expertise in application of organoids as mini-patient avatars. | TA1: Therapy recommendation techniques; |
| EMPAIA International e.V. | Norman Zerbe | norman.zerbe@empaia.org | nora.enzlberger@empaia.org | Berlin, Germany | EMPAIA International is dedicated to advancing multi-modal diagnostics through AI in healthcare. EMPAIA stands for EcosysteM for Pathology Diagnostics with AI Assistance We promote validated AI solutions for routine use by healthcare professionals while advocating for the removal of regulatory and technical barriers. Standardization in digital pathology, leveraging HL7/FHIR and DICOM, is a priority to facilitate broader adoption. As a non-profit organization, our 60 industry-partners benefit from networking opportunities across various stakeholders, including patients, physicians, pathologists, and policymakers. The organization represents members' interests in AI pathology concerning reimbursement and regulatory matters. We help to shape open-source standards for integrating AI into laboratory IT infrastructures and assist in implementing these standards for a seamless integration of AI into the clinical workflow. EMPAIA is an international non-profit organization with reference centers in Europe and Asia that is interested in impact of digitalization and AI on healthcare outcomes. | EMPAIA International seeks collaborative partners who share a commitment to advancing AI-driven diagnostics in healthcare. We particularly look for powerful partners with a strong focus on the US-market who are internationally established as well. Academic partners with diverse patient cohorts and expertise in clinical research are ideal for biomarker discovery and validation. Industry partners should be dedicated to developing biomarker-driven approaches for patient selection in clinical trials. Collaboration with partners who complement EMPAIA's capabilities in integrative multi-omics technologies, database development, and bioinformatics is highly valued. Together, we aim to accelerate the development and adoption of interoperable, open-source (MIT license), and innovative diagnostic solutions in diagnostic pathology to improve patient outcomes. | TA3: Treatment and analysis platform; |
| Biovica Inc | Amy Williams | amy.williams@biovica.com | San Diego, CA | Uncontrolled cell proliferation is the fundamental characteristic shared by all cancers. It is the goal of anti-cancer therapy to stop this growth. Biovica has developed an assay (DiviTim-TKa) that can quantify cell proliferation from a blood sample. The biomarker measured by the test is thymidine kinase activity (TKa), an enzyme only expressed during cell division. Measuring TKa levels before and during cancer therapy can provide information about prognosis, response to drug treatment, and in some cases inform therapy choice. The assay is FDA cleared and testing services are available for both commercial and research use. | We seek collaborations with cancer centers, drug developers, and other diagnostic assay companies. For cancer centers, we are open to research collaborations to explore the analysis of TKa in patient blood samples from completed or ongoing clinical trials to explore utility of TKa in new areas. For drug developers, we are interested in discussing the use of DiviTum as a dose optimization tool or a potential companion diagnostic to help identify responding patients. For diagnostic companies, we are interested in exploring whether additional analytes/biomarkers would complement the information from TKa and expand the utility. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; | |
| University of California San Diego | Tauhidur Rahman | trahman@ucsd.edu | San Diego CA | We aim to develop data ecosystem and models that will harness early disease trends and cancer therapy intervention efficacy from large-scale passive and continuous wearable and mobile sensor data. We want to develop the next generation "Fitbit step count" equivalent score for early cancer diagnosis and therapeutics. | Any team who wants to partner with someone who can bring in extensive experience on Large scale mobile sensor data. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; | |
| AtlasXomics | Katelyn Noronha | katelynn@atlasxomics.com | bd@atlasxomics.com | New Haven, CT | AtlasXomics is helping researchers understand the delicate epigenetic interplay and networks between cell types in their native environment that drives disease pathogenesis. We have helped over 50 investigators in oncology, aging, and neuroscience among other fields to locate and characterize driving epigenetic mechanisms in the tissue microenvironment. These mechanisms underly disease states and treatment responses. AtlasXomics combines epigenomics (spatial ATAC-seq and spatial CUT&Tag) with histology to provide insight that is often missed by bulk or single cell genomic tools. Our technology is primed for multi-omics studies in the same tissue section that uniquely positions us to identify and verify functional epigenetic mechanisms with proteome and transcriptome output. Mapping the cellular environment with an unbiased epigenome focus is needed to bring research closer to ground truth in diseased tissue to improve success rates for therapeutic interventions. | We are interested in partnering with clinicians or researchers who utilize animal models or primary human tissue in their research. Ideal partners are interested in using epigenomics or multi-omics to characterize novel biomarkers, characterize the TME or tumor heterogeneity, understand responders vs. non-responders, and devise transformative therapeutic strategies. Collaborators may also be working to develop and characterize models to better understand factors influencing tumor cell state. | TA1: Therapy recommendation techniques; |
| Concarlo Therapeutics | Stacy W. Blain | stacyblain@concarlo.com | jenimperial@concarlo.com | Brooklyn, NY | Concarlo Therapeutics is a preclinical biotechnology company pioneering a new way to inhibit the three highest value targets in oncology, CDK4/6 and CDK2…creating the elusive triple CDK2/4/6 inhibitor. We focus on drugging the master regulator p27, which controls CDK2/4/6 and sits at the bottom of the oncogenic signals that run from the cell surface to the nucleus. p27’s control of CDK2/4/6 is well validated, but we are the first company that has successfully been able to inhibit it, to indirectly inhibit CDK2/4/6. We have both large and small molecule assets in our pipeline. We are also developing diagnostics to identify patients that do not respond to the CDK4/6 inhibitors, such as Palbociclib, but would be candidates for our therapeutics. | We have shown that monitoring p27 phosphorylation status is a biomarker of CDK4/6i response. We have shown that when patients respond to Palbociclib, the high level of p27 phosphorylation, which signifies high activity of CDK4/6, is turned off. However, when patients become resistant to Palbociclib, the level of p27 phosphorylation increases again. We want to develop this biomarker for use in both biopsy material assayed by immunohistochemistry, but also for use in CTC (circulating tumor cells). The CTC test would allow this to be used as an adaptive biomarker, identifying patients as resistance developed, and before it was visible via imaging analysis. We are looking for partners with expertise in biomarker development, proteomic analysis of CTC, and retrospective analysis of clinical trial samples. | TA1: Therapy recommendation techniques; |
| SolarisRTC LLC | Esther Abels | info@solarisrtc.com | Boston, MA | SolarisRTC LLC (Solaris Research Trials Clinic) is a globally recognized Digital Health Advisory Company with strong partnerships with European based companies. Specializing in Digital Pathology, we research regulatory and clinical pathways using regulatory and clinical science, to standardize data collection, data analysis and data presentation, as well as including standardized approaches in translational medicine to include underrepresented data in developing AI models to facilitate policy making in precision medicine. This to optimize regulatory review processes, the total product life cycle, clinical outcomes and clinical as well as economic utility in BioPharma. | We look for partners who have access to longitudinal data and who are interested in using standardization approaches to optimize data collection. SolarisRTC uses scientific research to challenge the status quo of policies. Our vision is that we need standardization and diverse reliable as well as accurate data to allow accurate diagnostic decision making for precision medicine. With our expertise in quality, and in regulatory and clinical science in the pharma and biotech industry, we are seeking complementary partners who can provide diverse data to optimize policies. | TA2: Evolutionary clinical trial;TA1: Therapy recommendation techniques;TA3: Treatment and analysis platform; | |
| DDx Foundation | Matthew Leavitt | matt@ddxfoundation.org | joanne@ddxfoundation.org | Cedar City, UT | The DDx Foundation focuses on empowering Healthcare Equity, democratizing access to advanced cancer diagnostic technology, and accelerating clinical research to improve patient outcomes. DDx focuses research on a standardized implementation of digital pathology in under resourced communities. DP implementation in most community hospitals and clinics has been hindered by the high costs of equipment and other resource constraints. Until now, the advantages of digital pathology are only available to those treated in well-funded health systems. We at the DDx Foundation developed a digital-tech collaborative model to address these hurdles for communities otherwise cut-off from Medicine’s “cutting-edge”. DDx is working with health providers in under-resourced communities to make digital transformation easy and affordable for providers, bringing the benefits of digital path to all patients. | We look for partners who: 1) want to develop and/or utilize a standardized workflow solution using collaboratively generated data, and / or 2) who are interested in using data for research and discovery, translational medicine and / or algorithm validation, and / or 3) want to transition to digital in an efficient way to provide patients access to cutting edge technology and research as well as earlier access to treatments. | TA2: Evolutionary clinical trial; |
| UNC Living Tissue Systems | Shawn Hingtgen | hingtgen@ad.unc.edu | albert_baldwin@med.unc.edu | Chapel Hill, North Carolina | Our multi-disciplinary team, which spans basic scientists and clinicians, has shown that living tissue substrates (LTS) are a new platform for modeling cancer which enables rapid functional testing of therapeutic agents. Our multi-disciplinary team has developed a series of LTS models for metastatic cancers: brain, ovarian, lung, and others. We have shown the effectiveness of this platform to identify new mechanisms of disease, accelerate early-stage drug development, and serve as an innovative functional approach to clinical precision oncology, where: 1) living substrates of normal tissue rapidly capture a patient’s fresh tumor tissue across primary, metastatic, low grade, and high grade diseases, and the fully intact tissue environment shapes the cancer into lesions with genetic and tumor composition that closely mirrors the native disease; 2) functional testing can be performed with a broad range of therapeutics, including conventional chemotherapies, radiotherapy, small molecule inhibitors, cell/gene therapies, and immunotherapies; 3) analysis of on-target tumor kill vs. off-target toxicity to normal tissue to identify the most (and least) effective treatment based on a summarized Drug Sensitivity Score (DSS); 4) our approach outperforms previous similar efforts: our zero-passage approach maintains the genetic and transcriptomic fidelity which is lacking in in vitro and organoid culture, and our artificial-intelligence driven DSS output can be generated within 5 days, far shorter than patient-derived xenograft mouse models. Thus, the LTS system is fast enough to guide decisions in the clinic and robust enough to support academic or commercial drug development. | In partnerships and integration into other proposals we would deploy our existing clinical tissue collection, functional testing, panels of agents, and rapid AI-driven readouts to add novel and impactful capabilities in areas that include: 1. Serving as a functional biomarker to guide patient enrollment and improved care that are complementary to TA2 and TA3. 2. Providing personalized functional readouts of drug response to guide decisions on therapy along the continuim of care that are complementary to TA1 and TA2. 3. Enabling high-fidelty testing on fresh patient tissue to define drug activity and mechanisms of resistance across clinical standards of care or new agents entering clinical testing that is complementary to TA1. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| The University of Texas MD Anderson Cancer Center | Bora Lim | blim@mdanderson.org | Houston, Texas | Utilizing a comprehensive approach that integrates proteogenomics, spatial omics, and liquid biopsy in the context of organ-specific vulnerability, OPTIMAS aims to develop precise patient-derived models for better understanding and treating advanced breast cancer. This 'bench-to-bedside-to-back-to-bench' methodology positions us at the forefront of precision oncology. | For proteogenomics, we hope to align with Baylor College of Medicine, who is already part of diagnostic team for TA2. For Special omics, we hope join our forces internally (MDACC), and externally (The University of Texas Southwestern). For liquid biopsy, we plan to work with The University of Texas Health Science Center at Houston. However, we are also open to work with various organizations and investigators to help promote precision oncology in Metastatic Breast Cancer. | TA2: Evolutionary clinical trial; | |
| Weill Cornell Medicine | Juan Miguel Mosquera | jmm9018@med.cornell.edu | vjc4001@med.cornell.edu | New York, NY | Precision Medicine infrastructure with research programs in different cancer types that leverage molecular pathology, computational biology, tumor organoids and other platforms, as well as a large clinical trial portfolio | Discovery and validation of relevant biomarker-driven therapeutic targets in cancer | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial; |
| Clarivate | Mark Hyer | mark.hyer@clarivate.com | Jonathon Brzezinski | Alexandria, VA | Clarivate consultants support pre-clinical and clinical research projects for both solid and blood cancers to identify biomarkers, stratify patient populations, reconstruct mechanisms of action and resistance, find other promising drug targets, and address many more research questions. As part of our services offerings, we routinely integrate raw and processed multi-modal molecular data with clinical metadata, model disease progression or assist in building the computational infrastructure needed for large-scale analyses. We utilize RWD to streamline clinical trials recruitment and understand the population eligible for clinical trials. Marketplace coverage • 500+ oncology related indications • 300+ oncology brands forecasted to date in 2022 • Epidemiology forecasts for oncology brands in 171 countries • 90+ publications and abstracts since 2019 in oncology • 100+ oncology HTA submissions supported over the last 10 years Our talented people • 100+ subject matter experts including oncology analysts, epidemiologists, data scientists and consultants Clinical footprint • 8,000+ oncology molecular mechanisms of action • 99,000 oncology clinical biomarkers • 180,000+ oncology novel chemical compounds indexed • 50,000+ oncology chemical compounds indexed • 7,000+ distinct adverse events in oncology • 1M+ safety alerts related to adverse events in oncology Customer coverage • 140+ oncology patient populations • 1M+ RWD cancer patient lives • 2,000 oncologists surveyed annually • 300 oncology KOLs surveyed annually | Clarivate is looking to join ADAPT teams as a data/service provider to advance innovation. Examples: • Provide deep therapeutic level experts with industry experienced consultants to overlay our in-house data with context. • De-risk projects with drug development, safety, regulatory, and clinical trials analytics with expert guidance. • Conduct market research to ensure projects will be impactful and not repetitive. • Identify key potential triggers and inflection points along the patient journey to better understand the patient experience and inform physician messaging. • Pinpoint patient and physician unmet needs to better serve the customer and support value messaging. • Understand the complete disease landscape and size markets with real world data • Identify current lines of therapy, switching trends, and drug shares for indications • Provide coverage of clinical trials for every therapy area, including rare disease and orphan drug trial data not found elsewhere, paired with biomarker uses and patient segments • Utilizing 41B claims capturing care utilization for 300M+ patients , provide coverage of 1000+ specialty drug formulations across targeted therapeutic areas, rare diseases, and conditions • Identify current lines of therapy, adherence, switching trends, and drug shares for indications • Determine unmet needs, delays, and pain points in the patient experience across the diagnosis and treatment journey | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| EnteroTrack LLC | Robin Shandas | robin.shandas@enterotrack.com | Aurora, CO | Extremely low cost (<$1/device) method to simultaneously sample multiple biomarkers, microbiome, DNA, RNA and metabolome in the upper gut using a single, simple-to-use, non-endoscopic string-in-capsule procedure (the EnteroTracker). The device consists of a small capsule, with a proprietary collection string wound inside. Subject/patient swallows the capsule and the collection string unwinds through the esophagus, stomach, and small intestine. There is no need for sedation, specialized facilities, advanced training, or expense. Multiple clinical studies show the device is well tolerated, collects location specific samples without contamination, and can be administered in an office visit or even at home. Our company is the only producer of the EnteroTracker in the world, holds all patent rights to the technology, and is looking for partners in the cancer space. The device is a minimal-risk, class 1, 510(k)-exempt product. A smaller version of the EnteroTracker was recently released for clinical monitoring of patients with Eosinophilic Esophagitis (EoE). Multiple clinical trials are currently ongoing including evaluation of EoE in oral immunotherapy (OIT), non-invasive collection of biliary metabolites, evaluation of the nutritional metabolome, and longitudinal monitoring of the upper gut microbiome. Recently collected data shows clear differences between string-collected microbiome and stool microbiome. | We have produced an extremely scalable, clinically-validated device to non-endoscopically collect multiple biomarkers simultaneously from the gut without need for specialized facilities, equipment or training. The device can be sent to a remote clinic or a subject’s home for sample collection. It can be produced at scale for less than $1/device. We believe this device could be tremendously useful for large-scale clinical studies evaluating gut microbiome and other GI / immune mucosal biomarkers and for longitudinally monitoring and thereby personalizing therapies wherein multiple biomarkers from multiple locations in the gut need to be acquired. It can be used in remote / rural / low-resource locations easily. It is highly forgiving in that it is easy to use and any mistakes in usage do not carry any significant risk to the subject or administrator. We need funding to develop the manufacturing scale-up to support production of the devices at scale, with the goal of automating and optimizing manufacturing to support sale of the product at <$1/device. We have all regulatory, quality, and design controls in place. | TA2: Evolutionary clinical trial; | |
| Cellepus Therapeutics | Gabriel Gutierrez | gabe@cellepustx.com | jim@cellepustx.com | Rockville, MD | Cellepus Therapeutics is pre-clinical, seed stage biotech company developing a molecular toolkit to engineer “off-the-shelf” CAR-T cell therapies to safely treat solid tumors. While current CARTs have revolutionized blood cancer therapy, they have been unable to treat solid tumors safely and effectively, which represent more than 80% of cancers. To address the shortcoming of CAR-T therapies in solid tumors, Cellepus created precision-guided γδ1/3 CAR-T cells with proprietary “Zeta-less” CAR signaling architecture that resists exhaustion intrinsic to traditional Cd28/41BB frameworks. Indeed, γδ1/3 cells’ innate ability to seek, penetrate, and kill solid tumors is a significant advantage to circulating ab and γδ2 T cells. Further, we have developed an isolation process from healthy cord-blood donors that allows for a robust manufacturing process from stem cell-like populations for our allogeneic (“off-the-shelf”) drug product. To overcome potentially lethal, on-target/off-tumor effects of CAR-T targeting antibodies we conducted three patient-based antigen discovery campaigns, which yielded several truly tumor-specific candidates. Altogether, our “turbocharged” allogeneic γδ1/3 CAR-Ts can tackle cell therapy's solid tumor impasse. Our lead candidate, gd1-NKG2D-OR2, looks to safely and effectively kill a wide range of solid epithelial tumors including cholangiocarcinoma, ovarian, lung, prostate, breast and other carcinomas. | Cellepus is interested in collaborating with organizations to support the optimization and validation of several of our novel Tumor Specific Antigens (TSA), for which we have yet to fully characterize. Based on our screening campaigns and selection algorithms we are confident will can identify effective targets that may be highly specific and potent for select solid tumor types. Further, partnerships with GMP CAR T manufacturing organizations with expertise in TIL isolation, expansion, and access to cord blood would be ideal. Furthermore, we would be keen to identify groups to help support diagnostic development and validation as the importance of this expertise is crucial for guiding treatment decisions, improving patient outcomes, and assuring our candidates succeed. | TA3: Treatment and analysis platform; |
| University of Connecticut School of Medicine | Pramod K. Srivastava MD PhD | srivastava@uchc.edu | mcallahan@uchc.edu | Farmington, CT | Our focus is on cancer vaccines and cancer immunotherapy. Three areas of focus: (1) cancer neoepitopes: we have a strong program of neoepitope discovery using multiple mouse models, as well as selected human cancers, using state of the art tools in genomics and bioinformatics as well as excellent immunological tools (see Srivastava 2024 journal of Clinical Investigation). (2) Immunotype as biomarker: Immunotype (as characterized by expression of LAG3 and other markers on CD8 T cells) is a novel and rigorous biomarker for response to immune checkpoint blockade, identified by Dr. Margaret Callahan at our organization. It continues to be investigated and developed clinically and mechanistically (see Shen et al. 2021 Science Translational Medicine). (3) T cell receptor-MHC-peptide affinity and avidity, as it bears of immune response to cancer in mouse models and human cancer is a major focus (see Singhaviranon et al. 2023 Journal o Immunology). | We are looking to partner with a team conducting clinical trials in non small cell lung cancers, colon cancers or breast cancers using any treatment modality. We do have a special interest in immunotherapy, but are interested in other areas of therapy as well. We would like obtain a small amount of resected tumor tissue from which we can isolate CD8+ tumor infiltrating lymphocytes (TIL). Because of logistical issues, it would be best if the TIL isolation could be carried out at the teaming partner site itself. We have developed a CD8 T cell transcriptomic signature that is predictive of clinical response in extensive studies in mouse models and in preliminary studies in humans. This signature can be tested rapidly and in real time. We wish to test the predictive power of this signature panel in larger numbers of patients and in multiple cancer types. | TA1: Therapy recommendation techniques;TA3: Treatment and analysis platform; |
| UTHealth Houston | Assaf Gottlieb | assaf.gottlieb@uth.tmc.edu | Lenora.G.Trujillo@uth.tmc.edu | Houston, TX | The University of Texas Health Science Center at Houston (UTHealth) is one of the 14 institutions of the University of Texas system and is located at the Texas Medical Center - the largest medical complex in the world. Within the university, we are a group of researchers within the McWilliams School of Biomedical Informatics (MSBMI), which is the only school for BMI in the US. The school is focused on multiple domains of biomedical informatics research and interact with other health-related schools, including medical, nursing, public health and dental schools. Our team's expertise is on building computational models that combine artificial intelligence, bioinformatics and systems biology methods that will be developed to address drug resistance within the ADAPT initiative. | In teaming partners, we are looking to collaborate with teams focused on the clinical effort, to share clinical data that can be used to test and validate our models in the first phase, and help implement our models in clinical setting in the second phase. | TA1: Therapy recommendation techniques; |
| University of Connecticut Health | Kshitiz | kshitiz@uchc.edu | ldidden@uchc.edu | Farmington, Connecticut | Kshitiz Lab has pioneered a unique approach to use evolutionary medicine to treat/prevent cancer metatstasis. The lab has shown that cancer malignancy rates differ widely across mammals, and this phenomenon is due to the evolved resistance to placental invasion during gestation. This unique approach has spawned a research program to both understand human patient's response to cancer metastasis, as well as develop therapies to prevent cancer metastasis targeting the non-cancer cells. | We are looking for oncologists, dermatologists who can team up with us to provide tissue samples from different cancer types, as well as normal tissues. Our research program is already at a preclinical stage, and we are seeking collaborations with clinicians across the cancer field. | TA1: Therapy recommendation techniques;TA3: Treatment and analysis platform; |
| University of Massachusetts | Govind Srimathveeravalli | govind@umass.edu | Amherst, Massachusetts | Our research group within UMass studies biological response to electric fields, using knowledge gained to advance new technologies for tumor ablation, cancer diagnosis, tissue engineering and drug delivery. Our research is designed to be translation, starting with clear clinical problem that falls within the scope of tools in the lab. | We have developed technology that allows on-demand generation of a liquid sample enriched with high quality intracellular RNA, DNA and proteins. The sample can be generated from within defined tissue volumes (up to 3 cm diameter) and extracted with devices developed in our lab. Minor changes to the device would implantation for long-term monitoring and material extraction from tumors. Our technology is relevant for TA2.1, providing an on demand snapshot of the molecular status of the tumor. | TA2: Evolutionary clinical trial; | |
| Spring Science | Dr. Hope O'Donnell | hope@springscience.com | rrpv@springscience.com | San Carlos, CA | Spring Science is putting advanced AI image analysis tools in the hands of researchers across a broad spectrum of applications, using cellular or histologic morphology, phenomics, and proteomics to solve complex mechanisms, screen compound libraries, assess clinical biomarkers, and more. This platform is ideally suited to complex population response comparisons in primary cells, such as PBMC. In particular, we are interested in assessing predictive biomarkers at baseline, in response to in vitro treatment, and in response to in vivo treatment at multiple timepoints. Correlates between PBMC morphologic or proteomic biomarkers and other modalities, including histology and other imaging modalities, as well as other blood work results, would also be of interest. Spring’s custom AI analysis software integrates multiple data modalities in a way that could easily transition TA1 results into TA3 software. | Spring offers end-to-end experimental planning, imaging, and AI data analysis for a variety of primary cell types. Our 384-well imaging assay is optimized for minimal available cell numbers. Potential partners should have (or intend to have) access to human primary samples, such as frozen PBMC, relevant metadata (eg, test results, disease status, treatment outcomes, etc), and any drug candidates that cannot be commercially obtained, if required. | TA1: Therapy recommendation techniques;TA3: Treatment and analysis platform; |
| Yale University | Antonio Giraldez | antonio.giraldez@yale.edu | Linnea.weiss@yale.edu | New haven, CT | We have extensive expertise in RNA biology and computational biology and what to use this platform to develop more effective gene therapies, cancer therapies and vaccines. | Potential teaming partners include those with expertise in lipid nanoparticle and other delivery techniques for RNA | TA1: Therapy recommendation techniques; |
| Spatial Technologies Unit, Harvard Medical School Initiative for RNA Medicine, BIDMC | Ioannis Vlachos | ivlachos@bidmc.harvard.edu | Boston, MA | At the STU we generate and integrate single cell (fresh, frozen, FFPE), and spatial tissue profiling data (frozen, FFPE), using cutting-edge modalities and AI/ML. We have an intense focus on interactions within the tumor microenvironment and how it can be shaped by coding/non-coding variation, treatments, and cellular interactions. | Shared excitements about data generation and integration, especially from tissue samples and/or non-coding rnegions | TA1: Therapy recommendation techniques;TA3: Treatment and analysis platform; | |
| ImYoo | Tatyana Dobreva | tatyana@imyoo.health | dbrown@imyoo.health | South San Francisco, California | We are a patient-centric target and biomarker discovery platform that combines capillary blood self-collection with single-cell RNA sequencing. We generate high-fidelity molecular data longitudinally to identify novel responses and mechanisms necessary to create precision medicine. | We are looking for a partner either testing a treatment, or working with tissue. Our goal is to provide the longitudinal data in between treatments to increase chance of finding more effective biomarkers. | TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| Glendor Inc | Julia Komissarchik | julia@glendor.com | Draper UT | We at Glendor are on a quest to safeguard patients’ privacy by de-identifying Protected Health Information (PHI) automatically and at source. Glendor PHI Sanitizer - automatic in situ PHI De-identification software to protect patient’s privacy while empowering BAA-free data sharing and data monetization. Fully Automatic (unlike templates-based solutions that require customization and tweaking) At Source (unlike APIs and 3rd party services that require sensitive data to be shared) Easy to Integrate and Use (no BAA required, 1 min to install and run) Multiple Modalities Multiple Formats Medical Images (Pixels and Metadata) PDFs and Documents Videos and Photographs Voice Recordings and other Medical Data | We are looking for customers and partners who need to cleanse Protected Health Information (PHI) from their data. Use Cases: Medical Data Sharing; Medical Data Monetization; RWD/RWE Collection. Modalities: X-ray, Ultrasound, MRI, CT, PET, OCT, E2E, … Reports, Secondary Capture, … Videos, Dermatology Photos, Colonoscopy, … Dictations, Patient Interviews Recordings, … | TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; | |
| biomodal | Donna McDade Walker | donna.mcdadewalker@biomodal.com | jennifer.stone@biomodal.com | Cambridge, UK | biomodal is a life sciences tools company delivering the 6-base genome to better understand the dynamic nature of our epigenome and genome. Utilising single-base-resolution sequencing data and the interplay between A, C, G, T, 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) on the same molecule provides multimodal information that allows greater power in identifying novel biomarkers, detecting molecular tumour changes, and monitoring disease evolution; even with limited samples such as cell-free DNA (cfDNA). We have recently shown the utility of distinguishing and understanding the combination of these bases in an initial study of colorectal cancer (CRC) samples, where the effect of 5mC and 5hmC in enhancer regions of clinically relevant genes created distinct patterns in healthy individuals and tracked the move into stage I and through stage IV in CRC patients. The advanced 6-base genome data enables the exploration of epigenetic mechanisms of gene regulation through methylation and hydroxymethylation. By measuring multiple modes of biology from a single low-input DNA sample in a single experiment, you can use the comprehensive data to build predictive models of gene expression, chromatin accessibility, and enhancer status to better understand the biological mechanisms that link genotype to phenotype. | We’d enjoy collaborating with research and clinical-research partners who wish to better characterise & monitor samples by adding 6-base genome data to uncover predictive biomarkers, track disease progression and monitor response to therapeutics. Our solution provides a pre-sequencing workflow, and post-sequencing bioinformatics pipeline with data analysis suite. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial; |
| Genomic Expression | Gitte Pedersen | glp@genomicexpression.com | mlp@genomicexpression.com | Beverly, MA 01915 | We CLIA-validated quantitative RNA-seq of all mRNA in breast and ovarian cancer with 100% diagnostic yield, validated up against IHC and PCR. We typically identify 3-5 FDA-approved drugs in all patients enabling the repurposing of those drugs for the patients not responding to standard of care. The OneRNA® platform includes the following integrated technologies: 1) Chemistry enabling quantitative RNA-seq in clinical samples, such as paraffin-embedded tissue samples (FFPE) and liquid biopsy samples where RNA is fragmented/destroyed. 2) Identification of abnormal gene expression by comparing one patient's sample to a database of normal samples, eliminating the need for a second biopsy and removing amplification and sequencing bias. 3) Actionable report matching abnormally expressed genes to a proprietary database of all approved drug targets, ligands, and biomarkers Data is stored in a HIPAA and CLIA-compliant manner on AWS, and all sequencing analysis pipelines and reporting are fully automated, enabling Genomic Expression to send the report back to the physician in 1-2 weeks. The platform is disease and tissue-agnostic and exponentially scalable. Because the wetlab assay remains the same, the time and cost are dramatically reduced compared to validating disease-specific small panels. | We are looking for clinical partners/hospitals that are interested in implementing our OneRNA® platform in-house in the form of our OneRNA® kit and access to our OneRNACloud platform thereby upgrading their DNA panels. Alternatively they can send samples to us for analysis. This can greatly increase the identification of patients eligible for clinical studies and retain them at the institution when they no longer respond to standard of care. We are already working with some biotech and pharma companies to improve their clinical study design e.g. finding the right indication based on OneRNA® analysis of data across indications for penetration of their drug target or surface biomarker. We can also explore the competitive landscape leveraging our OneRNADrugDb. Finally, we can de-risk and accelerate clinical development by leveraging OneRNA® as a companion diagnostic AI-enabling platform, and develop multi-biomarker algorithms to effectively differentiate between responders and non-responders beyond what any single biomarker is capable of. Finally, we can find the right companion drug for a combinatorial clinical study in e.g. immune-oncology or exploring synthetic lethality mechanisms. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| SubjectWell | Jeremy Westfall | jeremy.westfall@subjectwell.com | nick.elvis@subjectwell.com | Austin, TX | We are one of the world's largest patient recruitment providers for clinical trials. We currently have 15M people seeking a clinical trial match with us and are adding 300K a month. | We are looking to help recruit patients for any / all clinical trials. | TA1: Therapy recommendation techniques;TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |
| BioPharma360 | Ivan Ballesteros | info@biopharma360.com | Sidra Shaikh | McLean, VA | BioPharma360 is a life science services and solutions company with over 35 combined years of industry experience. Our team is comprised of experts in multiple areas such as: Clinical Studies, Data Management, Project Management and Technology Solutions. We are equipped to provide the ADAPT support team with subject matter experts in clinical trial management including clinical project managers, clinical trial managers and research associates as well as experts in data management and project management. | BioPharma360 is looking for partners who have therapy research capabilities but are in need of support from clinical trial experts, data management and project management specialists. | TA2: Evolutionary clinical trial;TA3: Treatment and analysis platform; |