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Sample size determination in combinatorial chemistry.

P L Zhao1, R Zambias, J A Bolognese

  • 1Department of Biometrics Research, Merck Research Laboratories, Rahway, NJ 07065, USA.

Proceedings of the National Academy of Sciences of the United States of America
|October 24, 1995
PubMed
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This study analyzes the split/recombine method in combinatorial chemistry. It establishes a statistical method to determine the necessary number of polymer beads for controlling relative errors in compound library generation with high confidence.

Area of Science:

  • Medicinal Chemistry
  • Computational Chemistry
  • Statistical Analysis

Background:

  • Combinatorial chemistry is essential for generating molecular diversity.
  • The split/recombine method is a popular and efficient protocol for creating large compound libraries.
  • Accurate product distribution is crucial for library synthesis efficiency.

Purpose of the Study:

  • To assess the deviation from ideal equimolar distribution in split/recombine synthesis.
  • To establish statistical criteria for determining the required number of beads.
  • To ensure controlled relative errors in compound library generation.

Main Methods:

  • Utilized the split/recombine method for combinatorial library synthesis.
  • Applied Pearson statistic and chi-squared distribution to analyze product distribution errors.

Related Experiment Videos

  • Derived formulas to calculate the number of beads for specific error tolerances (L1 and L2).

    • Main Results:

    • The overall relative error in split/recombine synthesis is related to the Pearson statistic.
    • The Pearson statistic follows a chi-squared distribution, enabling statistical inference.
    • Quantified the number of beads required to achieve 99% confidence in controlling overall (L1) and individual (L2) relative errors.

    Conclusions:

    • The study provides a statistically sound method for optimizing split/recombine synthesis.
    • The derived criteria ensure high confidence in controlling product distribution errors.
    • This work is valuable for efficient and reliable generation of large compound libraries.