Quantitative Systems Pharmacology for Neuroscience Drug Discovery and Development: Current Status, Opportunities, and Challenges
The substantial progress made in the basic sciences of the brain has yet to be adequately translated to successful clinical therapeutics to treat central nervous system (CNS) diseases. Possible explanations include the lack of quantitative and validated biomarkers, the subjective nature of many clin...
Main Authors: | , , , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2020-01-01
|
Series: | CPT: Pharmacometrics & Systems Pharmacology |
Online Access: | https://doi.org/10.1002/psp4.12478 |
id |
doaj-8a1dd381fae0453582f85ba6ffbca2d2 |
---|---|
record_format |
Article |
spelling |
doaj-8a1dd381fae0453582f85ba6ffbca2d22020-11-25T03:16:22ZengWileyCPT: Pharmacometrics & Systems Pharmacology2163-83062020-01-019152010.1002/psp4.12478Quantitative Systems Pharmacology for Neuroscience Drug Discovery and Development: Current Status, Opportunities, and ChallengesHugo Geerts0John Wikswo1Piet H. van derGraaf2Jane P.F. Bai3Chris Gaiteri4David Bennett5Susanne E. Swalley6Edgar Schuck7Rima Kaddurah‐Daouk8Katya Tsaioun9Mary Pelleymounter10In Silico Biosciences Berwyn Pennsylvania USAVanderbilt Institute for Integrative Biosystems Research and Education Vanderbilt University Nashville Tennessee USACertara Canterbury UKCenter for Drug Evaluation and Research US Food and Drug Administration Silver Spring Maryland USARush Alzheimer's Disease Center Rush University Chicago Illinois USARush Alzheimer's Disease Center Rush University Chicago Illinois USABiogen Inc. Cambridge Massachusetts USAEisai Woodcliff Lake New Jersey USADepartment of Psychiatry and Behavioral Sciences Duke University Medical Center Durham North Carolina USAJohns Hopkins Bloomberg School of Public Health Baltimore Maryland USADivision of Translational Research National Institute of Neurological Disorders and Stroke Bethesda Maryland USAThe substantial progress made in the basic sciences of the brain has yet to be adequately translated to successful clinical therapeutics to treat central nervous system (CNS) diseases. Possible explanations include the lack of quantitative and validated biomarkers, the subjective nature of many clinical endpoints, and complex pharmacokinetic/pharmacodynamic relationships, but also the possibility that highly selective drugs in the CNS do not reflect the complex interactions of different brain circuits. Although computational systems pharmacology modeling designed to capture essential components of complex biological systems has been increasingly accepted in pharmaceutical research and development for oncology, inflammation, and metabolic disorders, the uptake in the CNS field has been very modest. In this article, a cross‐disciplinary group with representatives from academia, pharma, regulatory, and funding agencies make the case that the identification and exploitation of CNS therapeutic targets for drug discovery and development can benefit greatly from a system and network approach that can span the gap between molecular pathways and the neuronal circuits that ultimately regulate brain activity and behavior. The National Institute of Neurological Disorders and Stroke (NINDS), in collaboration with the National Institute on Aging (NIA), National Institute of Mental Health (NIMH), National Institute on Drug Abuse (NIDA), and National Center for Advancing Translational Sciences (NCATS), convened a workshop to explore and evaluate the potential of a quantitative systems pharmacology (QSP) approach to CNS drug discovery and development. The objective of the workshop was to identify the challenges and opportunities of QSP as an approach to accelerate drug discovery and development in the field of CNS disorders. In particular, the workshop examined the potential for computational neuroscience to perform QSP‐based interrogation of the mechanism of action for CNS diseases, along with a more accurate and comprehensive method for evaluating drug effects and optimizing the design of clinical trials. Following up on an earlier white paper on the use of QSP in general disease mechanism of action and drug discovery, this report focuses on new applications, opportunities, and the accompanying limitations of QSP as an approach to drug development in the CNS therapeutic area based on the discussions in the workshop with various stakeholders.https://doi.org/10.1002/psp4.12478 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hugo Geerts John Wikswo Piet H. van derGraaf Jane P.F. Bai Chris Gaiteri David Bennett Susanne E. Swalley Edgar Schuck Rima Kaddurah‐Daouk Katya Tsaioun Mary Pelleymounter |
spellingShingle |
Hugo Geerts John Wikswo Piet H. van derGraaf Jane P.F. Bai Chris Gaiteri David Bennett Susanne E. Swalley Edgar Schuck Rima Kaddurah‐Daouk Katya Tsaioun Mary Pelleymounter Quantitative Systems Pharmacology for Neuroscience Drug Discovery and Development: Current Status, Opportunities, and Challenges CPT: Pharmacometrics & Systems Pharmacology |
author_facet |
Hugo Geerts John Wikswo Piet H. van derGraaf Jane P.F. Bai Chris Gaiteri David Bennett Susanne E. Swalley Edgar Schuck Rima Kaddurah‐Daouk Katya Tsaioun Mary Pelleymounter |
author_sort |
Hugo Geerts |
title |
Quantitative Systems Pharmacology for Neuroscience Drug Discovery and Development: Current Status, Opportunities, and Challenges |
title_short |
Quantitative Systems Pharmacology for Neuroscience Drug Discovery and Development: Current Status, Opportunities, and Challenges |
title_full |
Quantitative Systems Pharmacology for Neuroscience Drug Discovery and Development: Current Status, Opportunities, and Challenges |
title_fullStr |
Quantitative Systems Pharmacology for Neuroscience Drug Discovery and Development: Current Status, Opportunities, and Challenges |
title_full_unstemmed |
Quantitative Systems Pharmacology for Neuroscience Drug Discovery and Development: Current Status, Opportunities, and Challenges |
title_sort |
quantitative systems pharmacology for neuroscience drug discovery and development: current status, opportunities, and challenges |
publisher |
Wiley |
series |
CPT: Pharmacometrics & Systems Pharmacology |
issn |
2163-8306 |
publishDate |
2020-01-01 |
description |
The substantial progress made in the basic sciences of the brain has yet to be adequately translated to successful clinical therapeutics to treat central nervous system (CNS) diseases. Possible explanations include the lack of quantitative and validated biomarkers, the subjective nature of many clinical endpoints, and complex pharmacokinetic/pharmacodynamic relationships, but also the possibility that highly selective drugs in the CNS do not reflect the complex interactions of different brain circuits. Although computational systems pharmacology modeling designed to capture essential components of complex biological systems has been increasingly accepted in pharmaceutical research and development for oncology, inflammation, and metabolic disorders, the uptake in the CNS field has been very modest. In this article, a cross‐disciplinary group with representatives from academia, pharma, regulatory, and funding agencies make the case that the identification and exploitation of CNS therapeutic targets for drug discovery and development can benefit greatly from a system and network approach that can span the gap between molecular pathways and the neuronal circuits that ultimately regulate brain activity and behavior. The National Institute of Neurological Disorders and Stroke (NINDS), in collaboration with the National Institute on Aging (NIA), National Institute of Mental Health (NIMH), National Institute on Drug Abuse (NIDA), and National Center for Advancing Translational Sciences (NCATS), convened a workshop to explore and evaluate the potential of a quantitative systems pharmacology (QSP) approach to CNS drug discovery and development. The objective of the workshop was to identify the challenges and opportunities of QSP as an approach to accelerate drug discovery and development in the field of CNS disorders. In particular, the workshop examined the potential for computational neuroscience to perform QSP‐based interrogation of the mechanism of action for CNS diseases, along with a more accurate and comprehensive method for evaluating drug effects and optimizing the design of clinical trials. Following up on an earlier white paper on the use of QSP in general disease mechanism of action and drug discovery, this report focuses on new applications, opportunities, and the accompanying limitations of QSP as an approach to drug development in the CNS therapeutic area based on the discussions in the workshop with various stakeholders. |
url |
https://doi.org/10.1002/psp4.12478 |
work_keys_str_mv |
AT hugogeerts quantitativesystemspharmacologyforneurosciencedrugdiscoveryanddevelopmentcurrentstatusopportunitiesandchallenges AT johnwikswo quantitativesystemspharmacologyforneurosciencedrugdiscoveryanddevelopmentcurrentstatusopportunitiesandchallenges AT piethvandergraaf quantitativesystemspharmacologyforneurosciencedrugdiscoveryanddevelopmentcurrentstatusopportunitiesandchallenges AT janepfbai quantitativesystemspharmacologyforneurosciencedrugdiscoveryanddevelopmentcurrentstatusopportunitiesandchallenges AT chrisgaiteri quantitativesystemspharmacologyforneurosciencedrugdiscoveryanddevelopmentcurrentstatusopportunitiesandchallenges AT davidbennett quantitativesystemspharmacologyforneurosciencedrugdiscoveryanddevelopmentcurrentstatusopportunitiesandchallenges AT susanneeswalley quantitativesystemspharmacologyforneurosciencedrugdiscoveryanddevelopmentcurrentstatusopportunitiesandchallenges AT edgarschuck quantitativesystemspharmacologyforneurosciencedrugdiscoveryanddevelopmentcurrentstatusopportunitiesandchallenges AT rimakaddurahdaouk quantitativesystemspharmacologyforneurosciencedrugdiscoveryanddevelopmentcurrentstatusopportunitiesandchallenges AT katyatsaioun quantitativesystemspharmacologyforneurosciencedrugdiscoveryanddevelopmentcurrentstatusopportunitiesandchallenges AT marypelleymounter quantitativesystemspharmacologyforneurosciencedrugdiscoveryanddevelopmentcurrentstatusopportunitiesandchallenges |
_version_ |
1724636687246557184 |