Predicting and Preventing Adverse Maternal and Child Outcomes of Opioid Use Disorder in Pregnancy

预测和预防妊娠期阿片类药物使用障碍的不良母婴结局

• 批准号: 10683849
• 负责人: Steven R. Plump
• 金额: $ 32.52万
• 依托单位: OPALGENIX, INC.
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10683849
• 关键词: ABCB1 gene; ADRB2 gene; Adopted; Adult; Adverse event; Age; Algorithms; American; Anxiety; Biological; Buprenorphine; COVID-19 pandemic; CYP2B6 gene; CYP2D6 gene; CYP3A4 gene; Candidate Disease Gene; Child; Clinical; Clinical Trials; Computer software; Data; Devices; Dose; Electronic Health Record; Future; Genes; Genetic; Genetic Predisposition to Disease; Genetic Risk; Genetic Variation; Genotype; Head; Hospital Costs; Hospitalization; Incidence; Individual; Infant; Institutional Review Boards; Intelligence; Length of Stay; Logistic Regressions; Long-Term Effects; Machine Learning; Medical Device; Medication Management; Mental Depression; Metabolic; Metabolism; Methadone; Morphine; Neonatal Abstinence Syndrome; Newborn Infant; Opioid; Opioid Receptor; Outcome; Overdose; Pathway interactions; Patients; Performance; Pharmaceutical Preparations; Pharmacogenomics; Phase; Physicians; Physiological; Postpartum Period; Predictive Analytics; Pregnancy; Pregnant Women; Prevention; Prospective Studies; Public Health; Publishing; Race; Relapse; Reporting; Risk; Risk Assessment; Risk Factors; Safety; Sensitivity and Specificity; Severities; Small Business Innovation Research Grant; Smoking; Technology; Time; Up-Regulation; Variant; Weight; Withdrawal; Withdrawal Symptom; Woman; adverse outcome; algorithm development; behavioral outcome; candidate validation; care costs; clinical development; clinical practice; clinical predictors; clinical risk; combinatorial; commercialization; cost; craving; economic outcome; experience; fetal opioid exposure; genetic predictors; genetic signature; genetic variant; high risk; improved; innovation; inter-individual variation; intrapartum; maternal anxiety; maternal depression; maternal opioid use; maternal risk; meetings; opioid epidemic; opioid use; opioid use disorder; outcome prediction; personalized intervention; personalized risk prediction; phase 2 study; polysubstance use; prediction algorithm; predictive tools; pregnant; prevent; primary outcome; programs; response; risk prediction; risk prediction model; secondary outcome; standard of care; unpublished works

PROJECT SUMMARY: Opioid Use Disorder (OUD) in pregnant women, Neonatal Opioid Withdrawal Syndrome (NOWS) and associated hospital costs have dramatically increased in the past decade, with an American child is born suffering from NOWS every 15 minutes. The ongoing opioid epidemic is further worsened by the COVID- 19 pandemic. Despite medication treatment for OUD with buprenorphine or methadone, the pregnant women continue to be at high risk for early relapse, polysubstance use, overdose, depression, poor outcomes, and associated high costs of longer hospital stays, and their significant negative long-term effects in women and their children. Maternal depression and anxiety increase the risks for OUD, maternal relapse and NOWS. Children with NOWS also experience poor long-term neurodevelopmental and behavioral outcomes. Genetic factors influence opioid-related adverse events and outcomes including OUD and NOWS. The current clinical practices for OUD treatment in pregnant women and NOWS do not include proactive risk prediction and prevention. There is no comprehensive and polygenetic clinically adoptable risk prediction tool to proactively identify risks for maternal relapse, NOWS and costly care. There is an urgent and unmet clinical need for a reliable technology to proactively predict maternal relapse, NOWS, and improve the safety of pregnant women with OUD and their children. We have shown that opioid related poor clinical outcomes vary significantly based on underlying genetic predisposition. Single gene variations are independently associated with OUD, NOWS and inter-individual variations in responses to buprenorphine, methadone and morphine, the commonly used opioids to treat OUD in pregnant women and NOWS in infants. OpalGenix will build on our extensive prior prospective studies of genetic and clinical predictors of opioid-related adverse outcomes to develop and commercialize a transformative device, OpalGenix’s Genotype-guided Physician Support for Opioids, GPS-OpioidTM. GPS-Opioid will be a 510(k) cleared predictive analytic software as a medical device consisting of polygenetic, clinical risk factors and electronic health record-integrated intelligent analytics to provide personalized risk analysis to proactively predict risk for OUD-related risks including maternal relapse and NOWS with high accuracy (>80%) to enable personalized interventions, significantly improve clinical outcomes while reducing costs of care. In this Phase I proposal, OpalGenix will build on these studies to develop and validate GPS Opioid as a 510(k) cleared algorithm (medical device) that innovatively integrates polygenetic and clinical risks (e.g., maternal depression) to proactively predict personalized risk for maternal relapse and NOWS. We will leverage our team’s expertise with opioid pharmacogenomics, maternal OUD, NOWS, combinatorial risk predictive algorithms and commercialization to reduce OUD related burden in pregnant women and their children. Completion of this Phase I program will demonstrate value for GPS Opioid to improve clinical and economic outcomes, support an FDA Investigational Device Exemption (IDE) application, and de-risk a Phase II head-to-head clinical trial.

项目摘要：孕妇阿片类药物使用障碍 (OUD)、新生儿阿片类药物戒断综合征 （NOWS）和相关的医院费用在过去十年中急剧增加，一名美国儿童 每 15 分钟就有一个出生的人患有 NOWS，持续的阿片类药物流行因新冠肺炎而进一步恶化。 19 大流行期间，尽管使用丁丙诺啡或美沙酮对 OUD 进行药物治疗，但孕妇 仍然处于早期复发、多种物质使用、用药过量、抑郁、预后不良和 较长住院时间带来的高额费用，以及对妇女及其她们的长期负面影响 母亲抑郁和焦虑会增加 OUD、母亲复发和NOWS 的风险。 患有NOWS 的人也会经历长期神经发育和行为结果不佳的遗传因素。 影响阿片类药物相关的不良事件和结果，包括 OUD 和NOWS 当前的临床实践。 孕妇的 OUD 治疗和NOWS 不包括主动风险预测和预防。 没有全面的、多基因的临床可采用的风险预测工具来主动识别风险 产妇复发、NOWS 和昂贵的护理 临床对可靠技术的需求迫切且尚未得到满足。 主动预测产妇复发，NOWS，并提高患有 OUD 的孕妇及其母亲的安全 我们已经证明，阿片类药物相关的不良临床结果因潜在遗传因素而有很大差异。 单基因变异与 OUD、NOWS 和个体间独立相关。 对丁丙诺啡、美沙酮和吗啡（治疗 OUD 的常用阿片类药物）的反应存在差异 OpalGenix 将建立在我们之前广泛的前瞻性研究的基础上。 阿片类药物相关不良后果的遗传和临床预测因素，以开发变革性药物并将其商业化 OpalGenix 的基因型引导阿片类药物 GPS-Opioid™ 医师支持将成为一种设备。 510(k) 批准预测分析软件作为包含多基因、临床风险因素和 电子健康记录集成智能分析，提供个性化风险分析以主动预测 OUD 相关风险的风险，包括产妇复发和NOWS，具有高精度 (>80%)，以实现 在第一阶段，个性化干预可显着改善临床结果，同时降低护理成本。 根据提案，OpalGenix 将在这些研究的基础上开发和验证 GPS 阿片类药物作为 510(k) 批准的算法 （医疗器械）创新性地将多遗传和临床风险（例如孕产妇抑郁症）整合到一起 我们将利用我们团队的专业知识，主动预测产妇复发的个性化风险。 阿片类药物基因组学、母体 OUD、NOWS、组合风险预测算法和 商业化以减少孕妇及其子女的 OUD 相关负担 完成此阶段。 I 计划将证明 GPS 阿片类药物在改善临床和经济成果方面的价值，支持 FDA 研究设备豁免 (IDE) 申请，并降低 II 期头对头临床试验的风险。