Inside the Mind of a Medicinal Chemist: The Role of Human Bias in Compound Prioritization during Drug Discovery
et al. (2012) Inside the Mind of a Medicinal Chemist: The Role of Human Bias in Compound
Prioritization during Drug Discovery. PLoS ONE 7(11): e48476. doi:10.1371/journal.pone.0048476
Inside the Mind of a Medicinal Chemist: The Role of Human Bias in Compound Prioritization during Drug Discovery
Peter S. Kutchukian 0
Nadya Y. Vasilyeva 0
Jordan Xu 0
Mika K. Lindvall 0
Michael P. Dillon 0
Meir Glick 0
John D. Coley 0
Natasja Brooijmans 0
Qianjun Li, University of Alabama at Birmingham, United States of America
0 1 Center for Proteomic Chemistry, Novartis Institutes for BioMedical Research , Cambridge, Massachusetts , United States of America, 2 Department of Psychology, Northeastern University , Boston , Massachusetts, United States of America, 3 Global Discovery Chemistry, Novartis Institutes for BioMedical Research, Emeryville, California, United States of America , 4 Blueprint Medicines, Cambridge, Massachusetts , United States of America
Medicinal chemists' ''intuition'' is critical for success in modern drug discovery. Early in the discovery process, chemists select a subset of compounds for further research, often from many viable candidates. These decisions determine the success of a discovery campaign, and ultimately what kind of drugs are developed and marketed to the public. Surprisingly little is known about the cognitive aspects of chemists' decision-making when they prioritize compounds. We investigate 1) how and to what extent chemists simplify the problem of identifying promising compounds, 2) whether chemists agree with each other about the criteria used for such decisions, and 3) how accurately chemists report the criteria they use for these decisions. Chemists were surveyed and asked to select chemical fragments that they would be willing to develop into a lead compound from a set of ,4,000 available fragments. Based on each chemist's selections, computational classifiers were built to model each chemist's selection strategy. Results suggest that chemists greatly simplified the problem, typically using only 1-2 of many possible parameters when making their selections. Although chemists tended to use the same parameters to select compounds, differing value preferences for these parameters led to an overall lack of consensus in compound selections. Moreover, what little agreement there was among the chemists was largely in what fragments were undesirable. Furthermore, chemists were often unaware of the parameters (such as compound size) which were statistically significant in their selections, and overestimated the number of parameters they employed. A critical evaluation of the problem space faced by medicinal chemists and cognitive models of categorization were especially useful in understanding the low consensus between chemists.
-
Funding: This work was supported by the Novartis Institutes for Biomedical Research, and P.S.K. is funded as a Presidential Postdoctoral Fellow by the NIBR
Education Office. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: P.S.K., J.X., M.K.L., M.G., and M.P.D. are employed by Novartis Institutes for BioMedical Research. N.B. is employed by Blueprint Medicines.
There are no patents, products in development or marketed products to declare. This does not alter the authors adherence to all the PLOS ONE policies on
sharing data and materials.
A core function of human cognition is to reduce the complexity
of the world to manageable proportions. In everyday life, we
ignore most of the information available in the environment in an
attempt to focus on what is likely to be most important. In some
professional contexts, this process is raised to an art form,
providing a useful context in which to investigate the human
cognitive response to complexity.
For instance, in research departments across the pharmaceutical
industry, medicinal chemists routinely sift through long lists of
compounds with associated data (biochemical activities,
physicochemical properties, etc.) in order to prioritize some for further
optimization or study, and discard others in the search for new
drug candidates. [1] Although computational tools have been
developed to aid compound prioritization, [2] medicinal chemists
remain intimately involved in compound review. In order to
prioritize compounds, chemists must consider whether they
possess desirable physical chemical properties (e.g., solubility),
how easily they can be synthetically accessed and chemically
manipulated, and whether they can be optimized to bind a desired
target while avoiding undesirable biological properties such as
offtarget interactions or mutagenicity. Indeed, guiding compounds
through all the potential pitfalls that lie between an initial
ensemble of hits and a drug candidate is an extremely complex
task, and the selection of the initial chemical starting points for this
endeavor greatly impacts the path that is explored, (...truncated)