Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer death in the United States with a median survival of <6 months and a 5-yr survival rate of 3%-8%. The aggressive biology and resistance to currently used therapeutic agents underscore the clear unmet need for the development of effective therapies against PDAC. Development of therapeutically important small molecules has benefited from computational drug discovery methods over three decades. However, these approaches suffer from significant limitations. twoXAR has developed a computational drug discovery approach that overcomes these limitations. Building on our prior success in identifying candidate drugs for hepatocellular carcinoma (HCC), we propose to use an artificial intelligence (AI) driven platform developed by twoXAR to identify new drug candidates as potential effective therapies for PDAC. In preliminary studies, we showed that TXR-311, a lead candidate selected based on our platform for efficacy against HCC significantly inhibited growth of: (a) HCC cell-lines, but not healthy hepatocytes and (b) orthotopic mouse HCC patient-derived xenografts (PDX). Moreover, (c) we also used our AI-based approach to predict validated candidates for rheumatoid arthritis (RA), multiple sclerosis (MS), and type 2 diabetes (T2D). The efficiency in drug discovery resulting from computational models provides an opportunity to build a portfolio of drug programs that traditional discovery methods don't allow for without hundreds of millions of dollars and many years. twoXAR?s approach to developing drug pipeline through partnerships and spin-outs enables us to apply our technology broadly across therapeutic areas, put drug development in the hands of expert drug developers, and create a portfolio of drug programs that significantly increases the probability of a twoXAR-discovered treatment benefiting patients. In the current Phase I SBIR proposal, we will identify candidate drugs to treat PDAC, using our platform. The specific aims are: Aim 1: Leverage twoXAR?s AI platform to identify lead candidates to treat PDAC. Milestone: Screen at least 100 hits that emerge based on aggregate scoring and identify at least 10 leads for further analysis and in vitro/in vivo validation. Aim 2: Use industry-standard preclinical assays to validate lead drug candidates. Milestone: Identification of a primary lead candidate for the treatment of PDAC. After successful completion of the proposed studies, we will develop the identified lead candidate for the treatment of PDAC through a Phase II SBIR mechanism to conduct mechanism of action (MoA), safety, and efficacy studies followed by early feasibility human studies, with the overarching goal of regulatory submission to the FDA and market commercialization.
Project Terms: Agar; Algorithmic Analysis; Algorithms; Area; Artificial Intelligence; Back; base; Benchmarking; Biological Assay; Biology; Body Weight decreased; Cancer cell line; Cancer Etiology; Cell Survival; Cessation of life; Chemicals; Clinical; clinical development; Clinical Research; commercialization; Computer Simulation; Computer software; cytotoxic; cytotoxicity; Data; Development; Disease; Disease model; Distant; drug candidate; drug development; drug discovery; Drug usage; Ductal Epithelial Cell; effective therapy; efficacy study; Ensure; Evaluation; Excision; experience; Financial cost; Future; Gene Expression; Genomics; Goals; Growth; hepatocellular carcinoma cell line; Hepatocyte; Histologic; Human; Immunofluorescence Immunologic; Immunohistochemistry; In Vitro; in vivo; Industry Standard; Knowledge; Lead; lead candidate; Lymphatic System; Malignant Neoplasms; Maximum Tolerated Dose; Methodology; Methods; Modeling; Molecular; Multiple Sclerosis; Mus; Mutation; Nature; neoplastic cell; Non-Insulin-Dependent Diabetes Mellitus; novel; novel therapeutics; oncology; Operative Surgical Procedures; Organ; Pancreatic Adenocarcinoma; pancreatic cancer cells; Pancreatic Ductal Adenocarcinoma; pancreatic neoplasm; Patients; Pharmaceutical Preparations; Pharmacology; Phase; pre-clinical; preclinical development; preclinical evaluation; Primary carcinoma of the liver cells; Probability; programs; Radiation therapy; Records; Reporting; Resistance; Reverse Transcriptase Polymerase Chain Reaction; Rheumatoid Arthritis; Safety; safety study; Small Business Innovation Research Grant; small molecule; Speed; Statistical Methods; success; Survival Rate; Systems Biology; Technology; Testing; Therapeutic; Therapeutic Agents; therapeutic development; Therapeutic Uses; tumor; tumor growth; Tumor Volume; tumor xenograft; United States; Validation; validation studies; virtual; Western Blotting; Work; Xenograft Model; Xenograft procedure;
