Predicting and Preventing Adverse Maternal and Child Outcomes of Opioid Use Disorder in Pregnancy
Predicting and Preventing Adverse Maternal and Child Outcomes of Opioid Use Disorder in Pregnancy
批准号:
10683849
负责人:
Steven R. Plump
金额:
$32.52万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-05-01 至 2025-04-30
关键词:
ABCB1 geneADRB2 geneAdoptedAdultAdverse eventAgeAlgorithmsAmericanAnxietyBiologicalBuprenorphineCOVID-19 pandemicCYP2B6 geneCYP2D6 geneCYP3A4 geneCandidate Disease GeneChildClinicalClinical TrialsComputer softwareDataDevicesDoseElectronic Health RecordFutureGenesGeneticGenetic Predisposition to DiseaseGenetic RiskGenetic VariationGenotypeHeadHospital CostsHospitalizationIncidenceIndividualInfantInstitutional Review BoardsIntelligenceLength of StayLogistic RegressionsLong-Term EffectsMachine LearningMedical DeviceMedication ManagementMental DepressionMetabolicMetabolismMethadoneMorphineNeonatal Abstinence SyndromeNewborn InfantOpioidOpioid ReceptorOutcomeOverdosePathway interactionsPatientsPerformancePharmaceutical PreparationsPharmacogenomicsPhasePhysiciansPhysiologicalPostpartum PeriodPredictive AnalyticsPregnancyPregnant WomenPreventionProspective StudiesPublic HealthPublishingRaceRelapseReportingRiskRisk AssessmentRisk FactorsSafetySensitivity and SpecificitySeveritiesSmall Business Innovation Research GrantSmokingTechnologyTimeUp-RegulationVariantWeightWithdrawalWithdrawal SymptomWomanadverse outcomealgorithm developmentbehavioral outcomecandidate validationcare costsclinical developmentclinical practiceclinical predictorsclinical riskcombinatorialcommercializationcostcravingeconomic outcomeexperiencefetal opioid exposuregenetic predictorsgenetic signaturegenetic varianthigh riskimprovedinnovationinter-individual variationintrapartummaternal anxietymaternal depressionmaternal opioid usematernal riskmeetingsopioid epidemicopioid useopioid use disorderoutcome predictionpersonalized interventionpersonalized risk predictionphase 2 studypolysubstance useprediction algorithmpredictive toolspregnantpreventprimary outcomeprogramsresponserisk predictionrisk prediction modelsecondary outcomestandard of careunpublished works
中文摘要
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英文摘要
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.
期刊论文(0)
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科研奖励(0)
会议论文
Avoiding Adverse Opioid Outcomes with Proactive Precision Care
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批准号:10541694
-
项目类别:
-
资助金额:$5.5万
-
财政年份:2021
-
负责人:Steven R. Plump
-
依托单位:
Avoiding Adverse Opioid Outcomes with Proactive Precision Care
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批准号:10257711
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项目类别:
-
资助金额:$31.94万
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财政年份:2021
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负责人:Steven R. Plump
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依托单位: