The correct amount of solubility is a key part in the search for new drugs to tackle diseases. This handbook provides data analysis of published solubility measurements of FDA recently-approved drugs methodically searched in recent years. Artificial intelligence and Bayesian statistics will likely be key to this subject area in the future.
The correct amount of solubility is a key part in the search for new drugs to tackle diseases. This handbook provides data analysis of published solubility measurements of FDA recently-approved drugs methodically searched in recent years. Artificial intelligence and Bayesian statistics will likely be key to this subject area in the future.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Alex Avdeef has been an American Association of Pharmaceutical Scientists (AAPS) Fellow since 2014, a former visiting senior research fellow at King's College London, and is the author of Absorption and Drug Development (2nd ed., Wiley, 2012). In 2021, the book was translated into Chinese, by translators affiliated with the China Food and Drug Administration. For nearly 50 years, he has been teaching, researching, and developing methods, instruments, and analysis software for the measurement of ionization constants, solubility, dissolution, and permeability of drugs. His accomplishments in the development of instrumentation include several well-known instruments that are or recently have been manufactured by leading companies in the instrument market, including Thermo Fisher Scientific, Sirius Analytical, and Pion Inc. He has over 200 technical publications in primary scientific journals and book chapters. He has written several comprehensive technical guides and is a coinventor on six patents. He cofounded Sirius Analytical (UK) in 1989, pION Inc. (USA) in 1996, and founded in-ADME Research (New York City) in 2011. His other positions were at Orion Research, Syracuse University, UC Berkeley, and Caltech.
Inhaltsangabe
1 Introduction 1.1 'Not too little - not too much', 1.2 Why a Database of Aqueous Intrinsic Solubility? 1.3 Database 1.4 Measurements Can Be Improved 1.5 Solubility-pH Profiles, Intrinsic Solubility, and Profile Distortions 2 Physicochemical Properties of Wiki-pS0 Database Molecules 2.1 Most Molecules in Database are Drug-Like or Drug-Relevant 2.2 Distribution of Intrinsic Solubility 2.3 Interlaboratory Variance 2.4 Quality and Chemical Space of Experimental Data 2.5 PROTACs: Lipinski's 'Rule Of 5' Characteristics 2.6 Newly-Approved Drugs: Lipinski's 'Rule Of 5' Characteristics 2.7 Kier Flexibility Index, , and Abraham H-Bond Acceptor Potential, B 2.8 Principal Component Analysis 2.9 Quantitative Estimate of Drug-Likeness 3 Solubility Prediction Methods 3.1 Overview of Solubility Prediction Models 3.2 Gap between Prediction and Measurement 3.3 Yalkowsky General Solubility Equation (GSE) 3.4 'Flexible-Acceptor' General Solubility Equation, GSE( ,B) 3.5 Abraham Solvation Equation (ABSOLV) 3.6 Breiman Random Forest Regression 4 Predicting of Solubility of PROTACs 4.1 Determination of the Three GSE( ,B) Coefficients from Training Set Iso-( +B) Bins 4.2 'Flexible-Acceptor' Lipophilicity 4.3 ABSOLV Trained to Predict the Intrinsic Solubility of PROTACs 4.4 RFR Training 4.5 Training Set Performances 4.6 Effect of Small Amounts of DMSO ( 5 vol%) 4.7 Predicting Solubility of PROTACs 5 Predicting of Solubility of New Drugs 5.1 Trends in Physicochemical Properties of Emerging Drugs 5.2 Characteristics of Emerging Drugs (2016-2022) 5.3 Re-training of the Training Sets 5.4 Predicting Solubility of Newly-Approved Drugs 5.5 Striving for Similarity Between Training Set and Test Set 6 Instruments with 'Intelligence' 6.1 Bjerrum Difference Plots for Saturated Solutions - Normalized Titration Curves 6.2 'Intelligent' Assay: Noyes-Whitney 'Dissolution Titration Template' (DTT) Method 6.3 High-Throughput Solubility Instrument with DMSO Bias Correction 6.4 Where to Aim Next Appendix - Data Sources, Solubility Definitions, Unit Conversions A1 Data Sources in Wiki-pS0 Database A1.1 'Kinetic Solubility' Measurements A1.2 Data for FDA Newly-Approved Drugs (2016-2022) A1.3 Data from Secondary Sources A.1.4 Single-Source Measurements A1.5 Data from Miscellaneous Primary Sources A1.6 Sources of pKa Data A2 Definitions, Supersaturation, Cosolvents A2.1 Consensus Recommendations A2.2 pH Measurement A3 Solubility Units - Conversions to Molarity A4 Different Types of Aqueous Solubility of Ionizable Molecules A4.1 Single-Point Water Solubility of Free Acid/Base (S /Sß for Free Acid/Base, or Simply Sw) A4.2 Single-Point Solubility at a Particular Buffered pH (SpH) A4.3 Single-Point Intrinsic Solubility (S0) A4.4 Single-Point Water Solubility of Non-Disproportionating -Type Salt ( Ssalt or S ) A4.5 Single-Point Water Solubility of Disproportionating -Type Salt (S ) General References Tabulation Organization and Notes TABULATION 1 - Wiki-pS0 TABULATION 2 - DMSO Bias-Corrected Solubility Tabulation References Index of Topics Index of Molecule Names Index of Registry Numbers (RN)
1 Introduction 1.1 'Not too little - not too much', 1.2 Why a Database of Aqueous Intrinsic Solubility? 1.3 Database 1.4 Measurements Can Be Improved 1.5 Solubility-pH Profiles, Intrinsic Solubility, and Profile Distortions 2 Physicochemical Properties of Wiki-pS0 Database Molecules 2.1 Most Molecules in Database are Drug-Like or Drug-Relevant 2.2 Distribution of Intrinsic Solubility 2.3 Interlaboratory Variance 2.4 Quality and Chemical Space of Experimental Data 2.5 PROTACs: Lipinski's 'Rule Of 5' Characteristics 2.6 Newly-Approved Drugs: Lipinski's 'Rule Of 5' Characteristics 2.7 Kier Flexibility Index, , and Abraham H-Bond Acceptor Potential, B 2.8 Principal Component Analysis 2.9 Quantitative Estimate of Drug-Likeness 3 Solubility Prediction Methods 3.1 Overview of Solubility Prediction Models 3.2 Gap between Prediction and Measurement 3.3 Yalkowsky General Solubility Equation (GSE) 3.4 'Flexible-Acceptor' General Solubility Equation, GSE( ,B) 3.5 Abraham Solvation Equation (ABSOLV) 3.6 Breiman Random Forest Regression 4 Predicting of Solubility of PROTACs 4.1 Determination of the Three GSE( ,B) Coefficients from Training Set Iso-( +B) Bins 4.2 'Flexible-Acceptor' Lipophilicity 4.3 ABSOLV Trained to Predict the Intrinsic Solubility of PROTACs 4.4 RFR Training 4.5 Training Set Performances 4.6 Effect of Small Amounts of DMSO ( 5 vol%) 4.7 Predicting Solubility of PROTACs 5 Predicting of Solubility of New Drugs 5.1 Trends in Physicochemical Properties of Emerging Drugs 5.2 Characteristics of Emerging Drugs (2016-2022) 5.3 Re-training of the Training Sets 5.4 Predicting Solubility of Newly-Approved Drugs 5.5 Striving for Similarity Between Training Set and Test Set 6 Instruments with 'Intelligence' 6.1 Bjerrum Difference Plots for Saturated Solutions - Normalized Titration Curves 6.2 'Intelligent' Assay: Noyes-Whitney 'Dissolution Titration Template' (DTT) Method 6.3 High-Throughput Solubility Instrument with DMSO Bias Correction 6.4 Where to Aim Next Appendix - Data Sources, Solubility Definitions, Unit Conversions A1 Data Sources in Wiki-pS0 Database A1.1 'Kinetic Solubility' Measurements A1.2 Data for FDA Newly-Approved Drugs (2016-2022) A1.3 Data from Secondary Sources A.1.4 Single-Source Measurements A1.5 Data from Miscellaneous Primary Sources A1.6 Sources of pKa Data A2 Definitions, Supersaturation, Cosolvents A2.1 Consensus Recommendations A2.2 pH Measurement A3 Solubility Units - Conversions to Molarity A4 Different Types of Aqueous Solubility of Ionizable Molecules A4.1 Single-Point Water Solubility of Free Acid/Base (S /Sß for Free Acid/Base, or Simply Sw) A4.2 Single-Point Solubility at a Particular Buffered pH (SpH) A4.3 Single-Point Intrinsic Solubility (S0) A4.4 Single-Point Water Solubility of Non-Disproportionating -Type Salt ( Ssalt or S ) A4.5 Single-Point Water Solubility of Disproportionating -Type Salt (S ) General References Tabulation Organization and Notes TABULATION 1 - Wiki-pS0 TABULATION 2 - DMSO Bias-Corrected Solubility Tabulation References Index of Topics Index of Molecule Names Index of Registry Numbers (RN)
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