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Trends in PhysChem Properties of Newly Approved Drugs over the Last Six Years; Predicting Solubility of Drugs Approved in 2021

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A Correction to this article was published on 21 October 2022

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Abstract

For the ‘small-molecule’ NMEs (new molecular entities) approved in 2021 by the US FDA, quantitative solubility values were found for 28 drugs, nearly all from published New Drug Applications (NDAs). Comparisons of physicochemical properties over the last six years indicate that the NMEs are slowly continuing to increase in size and decrease in solubility. Since 2016, the intrinsic solubility values (S0) have decreased on average by 0.50 log10 unit, the calculated octanol–water partition coefficients (clogP) have increased by 0.34 log10 unit, and the molecular weights (MW) have increased by 22 g·mol−1 (to 477, compared to 298 in older drugs). The average number of H-bond acceptors has remained constant, while the average number of H-bond donors and the Kier Φ molecular flexibility indices have decreased slightly. The reported solubility data for the 2021 small-molecule NMEs were processed using the program pDISOL-X to obtain S0 values, normalized to 25 °C. The S0 values ranged from 2 ng·mL−1 (avacopan) to 43 mg·mL−1 (viloxazine). In the new set, MW spanned from 233 g·mol−1 (dexmethylphenidate) to 1215 g·mol−1 (voclosporin). Values of clogP ranged from − 0.3 (serdexmethylphenidate, a quaternary ammonium molecule) to 8.1 (avacopan). Five different in-silico models were used to predict the aqueous intrinsic log10 solubility of the 28 novel NMEs: (i) Yalkowsky’s General Solubility Equation (GSE(classic)), (ii) Abraham’s Linear Solvation Equation (ABSOLV), (iii) Avdeef–Kansy ‘Flexible-Acceptor’ General Solubility Equation ((GSE(Φ,B)), (iv) Breiman’s Random Forest Regression (RFR), and (v) consensus model based on (ii) and (iii) above. The various models were retrained with an enlarged version of the Wiki-pS0 database (currently at 7655 log10 S0 entries of drug-relevant molecules). The consensus model (r2 = 0.67, RMSE = 1.08) just slightly outperformed the other four models. The relatively simple consensus prediction equation can be easily incorporated into spreadsheet calculations. As new drugs are approved, it will be important to continue monitoring the quality of measured solubility. Matching prediction to measurement is valuable when prediction methods are applied to virtual libraries, in order to seek opportunities to minimize pharmacokinetic risks of large, but otherwise promising, candidate molecules.

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Change history

Abbreviations

S 0 :

Aqueous intrinsic solubility (i.e., the solubility of the uncharged form of the API)

S w :

Solubility of the pure API (active pharmaceutical ingredient) in pure water

n :

Number of measurements of log10 S0 in the training/test set

MPP:

The measure of prediction performance [77] refers to the percent of ‘correct’ predictions, as defined by the count of absolute residuals |log10 S obs0 – log10 S calc0 |≤ 0.5 divided by n. MPP is represented as a pie chart in the correlation plots (Fig. 5)

RMSE:

Root-mean-square error, accounting for bias in the prediction of external test set solubility values: RMSE = [1/(n − 1) Σi (y obsi  – y calci )2]1/2, where y = log10 S0

r 2 :

Coefficient of determination, accounting for bias in prediction of external test set solubility values [79]: r2 = 1 − Σi (y obs i – y calci )2 /Σi (y obsi —< y >)2, where y = log10 S0, and < y > is the mean value of observed log10 S0

bias:

Intercept in the regression fit: yobs = a + b ycalc, where the slope factor is fixed at unity

SD:

Standard deviation: SD = [1/n Σi (y obsi  − <y>)2 ]1/2, where <y> = mean value of log10 S0

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Acknowledgements

This study is dedicated to the memory of Professor Michael Abraham, whose pioneering work in the critical role of hydrogen bonding in solvation has influenced the authors deeply. The complete Wiki-pS0 database is planned to be released in book form: A. Avdeef. Intrinsic Aqueous Solubility—Critically Curated Data for Pharmaceutical Research (under discussion with publisher).

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  1. in-ADME Research, 1732 First Avenue #102, New York, NY, 10128, USA

    Alex Avdeef

  2. 79111, Freiburg Im Breisgau, Germany

    Manfred Kansy

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Avdeef, A., Kansy, M. Trends in PhysChem Properties of Newly Approved Drugs over the Last Six Years; Predicting Solubility of Drugs Approved in 2021. J Solution Chem 51, 1455–1481 (2022). https://doi.org/10.1007/s10953-022-01199-3

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