Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Quantitative risk modelling for new pharmaceutical compounds.

Zhengru Tang1, Mark J Taylor, Paulo Lisboa

  • 1School of Computing and Mathematical Sciences, Liverpool John Moores University, Liverpool L3 3AF, UK.

Drug Discovery Today
|November 1, 2005
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Association of cumulative early medical events and neurodevelopmental conditions through a common latent factor-A population-based twin study.

JCPP advances·2026
Same author

Reproductive health and healthcare experiences in autistic and non-autistic individuals assigned female at birth.

Women's health (London, England)·2026
Same author

Shared genetic and environmental influences between the broad avoidant/restrictive food intake disorder phenotype and neurodevelopmental traits: a twin study.

medRxiv : the preprint server for health sciences·2026
Same author

Associations between childhood somatic conditions and psychiatric diagnoses in autistic young adults: a retrospective, population-based cohort study in Sweden.

The Lancet. Child & adolescent health·2026
Same author

Association between co-occurring psychiatric conditions and premature mortality in autistic people: population-based cohort study.

The British journal of psychiatry : the journal of mental science·2026
Same author

The proportion of intellectual disability in autism spectrum disorder over two decades.

Psychiatry research·2026

Drug development is risky and expensive. This study presents a quantitative Bayesian Network model to assess drug candidate success probability, integrating manufacturing, clinical, and financial factors for better decision-making.

Area of Science:

  • Pharmaceutical sciences
  • Computational modeling
  • Risk analysis

Background:

  • Drug discovery and development is a lengthy, expensive, and high-risk process.
  • Identifying promising drug candidates requires careful resource allocation and informed decision-making.
  • Existing methods may not fully integrate manufacturing, clinical, and financial aspects of drug development risk.

Purpose of the Study:

  • To introduce a quantitative approach for modeling drug development risk.
  • To provide a tool for scenario analysis of a compound's probability of success.
  • To integrate manufacturing, clinical effectiveness, and financial returns into a unified risk model.

Main Methods:

  • Application of a Bayesian Network.
  • Development of a simulation model.

Related Experiment Videos

  • Implementation using MS Excel and the Crystal Ball modeling engine.

    • Main Results:

    • Demonstration of a quantitative risk modeling approach.
    • Integration of key drug development strands (manufacture, clinical effectiveness, financial returns).
    • A simulation model for scenario analysis of drug candidate success probability.

    Conclusions:

    • The developed quantitative approach offers a valuable tool for strategic decision-making in drug development.
    • Bayesian Networks can effectively model complex risks in pharmaceutical development.
    • This integrated model aids in targeting resources for compounds with higher probability of success.