Reinforcement learning for systems pharmacology-oriented and personalized drug design
Ryan K. Tan, Yang Liu, Lei Xie
Abstract
INTRODUCTION: Many multi-genic systemic diseases such as neurological disorders, inflammatory diseases, and the majority of cancers do not have effective treatments yet. Reinforcement learning powered systems pharmacology is a potentially effective approach to designing personalized therapies for untreatable complex diseases. AREAS COVERED: In this survey, state-of-the-art reinforcement learning methods and their latest applications to drug design are reviewed. The challenges on harnessing reinforcement learning for systems pharmacology and personalized medicine are discussed. Potential solutions to overcome the challenges are proposed. EXPERT OPINION: drug design.
Topics & Concepts
Reinforcement learningPersonalized medicineReinforcementDrug discoveryDrugSystems pharmacologyComputer scienceNeuroscienceMedicinePharmacologyBioinformaticsArtificial intelligencePsychologyBiologySocial psychologyGene Regulatory Network AnalysisViral Infectious Diseases and Gene Expression in InsectsComputational Drug Discovery Methods