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Analysis of recurrent research pathways for assessing and improving effectiveness in life sciences laboratories
E Andrew Balas1, Charmi Patel2, Ben Ewing2
1Biomedical Research Innovation Laboratory at Augusta University GA.
Background:
Life sciences research often turns out to be ineffective. Our aim was to develop a method for mapping repetitive research processes, detecting practice variations, and exploring inefficiencies.
Methods:
Three samples of R&I projects were used: companion diagnostics of cancer treatments, identification of COVID-19 variants, and COVID-19 vaccine development. Major steps involved: defined starting points, desired end points; measurement of transition times and success rates; exploration of variations, and recommendations for improved efficiency.
Results:
Over 50% of CDX developments failed to reach market simultaneously with new drugs. There were significant variations among phases of co-development (Bartlett test P<0.001). Length of time in vaccine development also shows variations (P<0.0001). Similarly, subject participation indicates unexplained variations in trials (Phase I: 489.7 (±461.8); Phase II: 857.3 (±450.1); Phase III: 35402 (±18079).
Conclusion:
Analysis of repetitive research processes can highlight inefficiencies and show ways to improve quality and productivity in life sciences.
Insights
Analyzing repetitive life science research processes reveals significant inefficiencies and variations. This method identifies areas for improvement to enhance research quality and productivity.
Area of Science:
- Life Sciences
- Biotechnology
- Pharmaceutical Research
Background:
- Life sciences research frequently faces effectiveness challenges.
- Inefficiencies in research and innovation (R&I) projects can hinder progress.
- A systematic approach is needed to identify and address these issues.
Approach:
- Developed a method to map repetitive research processes.
- Analyzed three R&I project samples: cancer companion diagnostics, COVID-19 variant identification, and vaccine development.
- Measured transition times, success rates, and explored variations in project phases and subject participation.
Key Points:
- Over 50% of companion diagnostic developments missed concurrent drug launches.
- Significant variations observed in co-development phases (Bartlett test P<0.001).
- Variations noted in vaccine development timelines (P<0.0001) and clinical trial subject participation.
Conclusions:
- Mapping repetitive research processes can uncover critical inefficiencies.
- Identifying practice variations is key to improving research quality.
- This analysis offers a pathway to boost productivity in life sciences.
