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Overcoming psychological barriers to good discovery decisions
Andrew T Chadwick1, Matthew D Segall
1Tessella Plc, Stanhope Bretby, Burton upon Trent, Staffs, UK. andrew.chadwick@tessella.com <andrew.chadwick@tessella.com>
Drug Discovery Today
|June 18, 2010
Summary
Cognitive biases can negatively impact research and development (R&D) decision-making, leading to increased costs and delays. Implementing evidence-based medicine principles and utilizing feedback in simulated environments can improve R&D team performance and objectivity.
Area of Science:
- Decision Science
- Cognitive Psychology
- Research and Development Management
Background:
- Cognitive biases are well-documented psychological phenomena that can impair objective decision-making.
- These biases pose significant risks to the efficiency and cost-effectiveness of research and development (R&D) processes.
- Unaddressed biases can lead to unexpected setbacks and inflated operational expenditures in R&D.
Purpose of the Study:
- To analyze the risks associated with common cognitive biases in R&D decision-making.
- To explore the application of evidence-based medicine principles as a model for mitigating bias in R&D.
- To identify potential strategies for enhancing objectivity and improving R&D outcomes.
Main Methods:
- Review of common cognitive biases and their specific impact on R&D decision-making.
- Comparative analysis of current R&D practices versus the structured approach of evidence-based medicine.
- Exploration of feedback mechanisms and computational tools for bias mitigation.
Main Results:
- Four prevalent cognitive biases were identified as particularly detrimental to R&D decision-making.
- Evidence-based medicine offers a framework for structured, objective decision-making applicable to R&D.
- Simulated environments providing performance feedback can enhance team decision-making in compound selection and screening.
Conclusions:
- Mitigating cognitive biases is crucial for improving R&D performance and reducing costs.
- Adopting principles similar to evidence-based medicine can foster greater objectivity in R&D.
- Feedback and computational tools show promise in supporting more rational and effective R&D decision-making.
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