High-throughput in-silico prediction of ionization equilibria for pharmacokinetic modeling

Estimates of ionization equilibrium constants (i.e., pKa) were analyzed for 8,132 pharmaceuticals and 24,281 other compounds to which humans might be exposed in the environment. Results revealed broad differences in the ionization of pharmaceutical chemicals and chemicals with either near-field (in the home) or far-field sources. Probability distributions corresponding to ionizable atom types (IATs) were then used to analyze the sensitivity of predicted Vdss on predicted pKa using Monte Carlo methods. 8 of the 22 compounds were predicted to be ionizable. For 5 of the 8 the predictions based upon ionization are significantly different from what would be predicted for a neutral compound. For all but one (foramsulfuron), the probability distribution of predicted Vdss generated by IAT sensitivity analysis spans both the neutral prediction and the prediction using ionization. This dataset is associated with the following publication: Strope, C., K. Mansouri, H. Clewell, J. Rabinowitz, C. Stevens, and J. Wambaugh. High-Throughput in-silico prediction of ionization equilibria for pharmacokinetic modeling. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 615: 150-160, (2018).

[
  "020:00"
]

[
  "020:095"
]

[
  "https://doi.org/10.1016/j.scitotenv.2017.09.033"
]