Physicochemical Properties in Small-Molecule Drug Discovery

GDD/TRD/PHAD/CPP author by

eLibrary “Drug-Likeness”: Physicochemical Properties in Small-Molecule Drug Discovery AndreaESCMID Decker, PhD Bootcamp on Medicinal Chemistry @ESCMID/ASM Conference Lisbon,© September 2018 Agenda

• Introduction “Drug-Likeness” author & Properties by

• Ionization • Lipophilicity • SolubilityeLibrary

• Summary & Conclusion ESCMID ©

28 What Makes a Small-Molecule into a Successful Drug? author by PD PK “Drug-likeness”: Intrinsic, structural properties that produce Dev eLibrary acceptable PK &Tox Tox

ESCMID © Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 3 Advantages of “Good” PK Properties Causes for failure in the clinic 2000-2010 author 1991 and 2000 by

eLibrary

Waring et al.: Kola & Landis: Nat. Rev. Drug Discov. 2004; 3(8); 711. Nat. Rev. Drug Discov. 2015; 14(7); 475. ESCMID  Control ©PK properties early to avoid failure later Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 4 Structure → Properties → Profile

Molecular Physicochemical Biochemical Pharmacokinetics (PK) target properties Properties Properties & Toxicity author property chemical clearance profile size by MW stability bioavailability shape solubility sp3 fraction # of rotatable bonds half-life flexibility permeability # of aromatic rings LD50 # of H-bonding eLibrary acceptors & donors metabolic polarity stability Off-target effects polar surface area logP plasma protein O lipophilicity pKa Cl OH binding structure H logD N ionization

Cl ESCMID  Modify structure© to obtain desired target property profile Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 5 Drug Discovery is a Multiparameter Optimization author by

eLibrary

ESCMID  Many parameters© are of interest, most are interconnected Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 6 Agenda

• Introduction “Drug-Likeness” author & Properties by

• Ionization • Lipophilicity • SolubilityeLibrary

• Summary & Conclusion ESCMID ©

28 Why We Care About Ionization solubility

PhysChem Properties (solubility, logD,...) authorPK properties (permeability, by metabolism,...)

aqueous solubility (log scale) acidic basic neutral Activity, potency hepatic clearance (on-target binding,...) selectivity @5µM pKa eLibrary clearance mL/min/kg Toxicity acidic basic neutral (selectivity, off- selectivity ratio target binding,...) Formulation acidic basic neutral ESCMID (solubility, salt formation,...)  Has major© effect on many properties and parameters Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 8 graphs from Charifson & Walters: J Med Chem 2014; 57(23): 9701. Ionization: Some Statistics

Oral marketed drugs Ionizable author 4% 5% Neutral 12% Always ionized by Others (salts/mixtures) 79%

eLibrary

 Most drugsESCMID are ionizable  Bases are© most common Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 9 Manallack et al.: Chem Soc Rev. 2013; 42(2); 485. pKa: The Fundamentals

• Ionization (protonation/deprotonation) can be considered as one of the simplest chemical (fast equilibrium)author reaction by

Acids: HA H++ A- Bases*: BH+ B + H+

= eLibrary

= 𝒑𝒑𝒑𝒑𝒂𝒂 −𝐥𝐥𝐥𝐥𝐥𝐥𝟏𝟏𝟏𝟏 𝑲𝑲𝒂𝒂 + − = + = [ ] 𝒂𝒂 𝑯𝑯 𝑨𝑨 𝑲𝑲 𝒂𝒂 𝑯𝑯𝑯𝑯 𝑯𝑯𝑯𝑯 + 𝒑𝒑𝒑𝒑 𝒑𝒑𝒑𝒑 𝒍𝒍𝒍𝒍𝒍𝒍 − ESCMID𝒑𝒑𝒑𝒑 −𝐥𝐥𝐥𝐥𝐥𝐥𝟏𝟏𝟏𝟏 𝑯𝑯 𝑨𝑨  When © = then [ ] = or [ ] = − + Drug Likeness: PhysChem Properties / Andrea𝒂𝒂 Decker / Lisbon, September 2018 10 𝒑𝒑𝒑𝒑 𝒑𝒑𝒑𝒑 𝑨𝑨 𝑨𝑨* For𝑨𝑨 bases, the conjugated𝑩𝑩𝑩𝑩 acid is considered𝑩𝑩 and its pKa is used Ionization depends on pH and pKa

100.0 O - O - AH A 80.0 AH A - Cl OH Cl O H H 60.0 author N N 40.0

20.0 by Cl Cl Diclofenac 0.0 Distribution of of (%) species Distribution 1.0 3.0 5.0 7.0 9.0 11.0 acid with pKa = 4.0 pH (concentration scale)

100.0 + BH+ BH B 80.0 B NH2 NH2 + O H2N O eLibraryHN 60.0 O O 40.0

20.0

OH Atenolol OH 0.0 base with pK = 9.5 of (%) species Distribution 1.0 3.0 5.0 7.0 9.0 11.0 a pH (concentration scale)  When , then species deprotonated (A- or B) © 𝒂𝒂 Drug Likeness: PhysChem𝒑𝒑𝒑𝒑Properties𝒑𝒑𝒑𝒑 / Andrea Decker / Lisbon, September 2018 11 𝒑𝒑𝒑𝒑 𝒑𝒑𝒑𝒑𝒂𝒂 Zwitterions

Ciprofloxacin: acidic pKa= 6.2 + basic pKa = 8.6 + ± - cation: ZH2 zwitterion: ZH authoranion: Z

+ + H2N H2N by HN N N N N N N

O O O F F - F - O OH O O O O

• Zwitterion : pseudo neutral, simultaneously charged + & - eLibrary isoelectric point • Multiple species co-exist 100.0 + ± - ZH2 ZH Z 80.0

60.0 ~ pH=6 50% + 50% + 0% 40.0

~ pH=7.4 5% + 90% + 5% 20.0 ESCMID 0.0 ~ pH=9 0% + 30% + 70% of (%) species Distribution 1.0 3.0 5.0 7.0 9.0 11.0 © pH (concentration scale) Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 12 pH- & Ionization-Dependent Property: Solubility author

Diclofenac Atenololby

O NH2 O HN Cl OH H O N

OH Cl acid eLibrarybase pKa = 4.0 pKa = 9.5

 Ionized speciesESCMID have a higher aqueous© solubility than neutral ones Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 13 pH- & Ionization-Dependent Property: Permeability

Diclofenac fraction ionized Simple membrane model: author phospholipid bilayer acid by pKa = 4.0 Permeability

eLibrary Desipramine fraction ionized base URL: https://cnx.org/contents/FPtK1zmh@ pKa = 10.6 8.108:q2X995E3@12/The-Cell-Membrane; Author: OpenStax Permeability

 Ionized speciesESCMID have a lower pH passive diffusion© permeability than neutral ones Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 14 adapted from: Wohnsland & Faller: J Med Chem 2001; 44(6): 923. Agenda

• Introduction “Drug-Likeness” author & Properties by

• Ionization • Lipophilicity • SolubilityeLibrary

• Summary & Conclusion ESCMID ©

28 Why We Care About Lipophilicity

• Has major effect on many PK and toxicity properties, as well as pharmacological activity author by solubility • Is a basic structural property metabolic permeability stability • “lipophilic”: greek λίπος "fat" & φίλοςeLibrary"friendly" lipophilicity

protein distribution binding

 logPoctanol/water : common estimateESCMID of lipophilicity toxicity © Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 16 logPoctanol/water: The Fundamentals

• instrinsic structural property of the molecule author • partition coefficient P: ratio of concentrations of neutral speciesby in two phases model for biological membranes (lipid octanol systems) eLibrary 0 X oct = 𝟎𝟎 𝒐𝒐𝒐𝒐𝒐𝒐 O water X0 𝑿𝑿 H H water 𝐥𝐥𝐥𝐥𝐥𝐥 𝑷𝑷 𝐥𝐥𝐥𝐥𝐥𝐥𝟏𝟏𝟏𝟏 𝟎𝟎 𝑿𝑿 𝒘𝒘 ESCMID  logP often© used for structure-property-relationship Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 17 logD: The Fundamentals

• logD combines lipophilicity (logP) & ionizability (pKa) author by

+ 0 XH oct X oct = 𝟎𝟎 𝑿𝑿 𝒐𝒐𝒐𝒐𝒐𝒐 𝐥𝐥𝐥𝐥𝐥𝐥 𝑷𝑷 𝐥𝐥𝐥𝐥𝐥𝐥𝟏𝟏𝟏𝟏 𝟎𝟎 + 0 𝑿𝑿 𝒘𝒘 XH water eLibraryX water + = = + + + + 𝟎𝟎 𝑿𝑿𝑿𝑿 𝑿𝑿𝑿𝑿 𝒐𝒐𝒐𝒐𝒐𝒐 𝑿𝑿 𝒐𝒐𝒐𝒐𝒐𝒐 𝒑𝒑𝒑𝒑𝒂𝒂 𝐥𝐥𝐥𝐥𝐥𝐥𝟏𝟏𝟏𝟏 𝟎𝟎 + 𝐥𝐥𝐥𝐥𝐥𝐥 𝑫𝑫 𝐥𝐥𝐥𝐥𝐥𝐥𝟏𝟏𝟏𝟏 + 𝟎𝟎 𝑿𝑿 𝑯𝑯 𝑿𝑿𝑿𝑿 𝒘𝒘 𝑿𝑿 𝒘𝒘  logD is pH ESCMIDdependent  logD@pHxyz  logD may© be better “predictor” for in-vivo properties Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 18 High-Throughput logP & [email protected] In-House Statistics • >7’000 logP & >11’000 logD datapoints (2015-2017) author by

eLibrary

logP logD

ESCMID © Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 19 logP & log D: Examples

Lasofoxifene Atenolol author logP = 5.8 logP = 0.8 [email protected] = 3.3 [email protected] = -0.2 by Diclofenac logP = 4.4 Chlorzoxazone [email protected] = 1.4 logP = 2.1 [email protected] = 2.1 eLibrary Atazanavir logP = 4.0 [email protected] = 4.0

Rifampicin / Rifampin clogP = 3.7 [email protected] = 0.9 © Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 20 Agenda

• Introduction “Drug-Likeness” author & Properties by

• Ionization • Lipophilicity • SolubilityeLibrary

• Summary & Conclusion ESCMID ©

28 Why We Care About Solubility

• One of the most important properties in drug development author • 70% of all sales for oral delivery by

• Key parameter for bioavailability

• Required for intravenous dosing absorption in eLibrary small intestines • Required for robust readout of bio-, PK-, toxicity-assays

bio- pharmacological solubility ESCMIDabsorption © availability efficacy & safety Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 22 Solubility in Drug Discovery: Dissolving Pebbles? • Comparison on how much dissolves in 1L of water author by

Daktarin (Miconazole) sugar 1.4 mg/L 2 kg / L (neutral form) (666 sugar cubes) salt eLibrary 350 g / L (23 table spoons) marble sand 14 mg / L 10 mg / L (50 grains) Cordarone (Amiodarone) x 17,000,000 x 100,000,000 ESCMID x 500 0.004 mg/L © (neutral form) Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 23 High-Throughput Eq. Solubility pH6.8 NIBR In-House Statistics • >30’000 compounds measured by HTSol over two years author

Project A pH6.8 Project Bby Project C ...... eLibrary

≤10 uM ≈ ≤ 5 mg/L 10−100 uM≈ 5−50 mg/L >100 uM≈ >50 mg/L ESCMID © Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 24 How the Physical Environment Can Affect Solubility

Solvent matrix authorpH e.g. which solvent, pure or mixture, additives,.... by

theo. max.: 10-fold per pH unit 1- to >1000-fold eLibrary Temperature

2- to >1000-fold < 2-fold for ∆T~15°C Solid state form ESCMID e.g. amorphous or crystalline © Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 25 How Structural Properties Can Affect Solubility Solute – Solvent Interactions  logP author (lipophilicity) 10-fold ↑ per log-unit ↓ by (empirical)*

 pKa 10-fold ↑ per 100ºC ↓ (empirical)* max. 10-fold ↑ per unit ↓ eLibrary  melting point Solid State Interactions Ionization (crystal packing) ESCMID *according to empirical “General Solubility see for example: B. Faller, P. Ertl, Advanced Drug Delivery Reviews 59 (2007) 533-545 Equation” by Y. Ran, N. Jain, S.H. Yalkowski, J. © Chem. Inf. Model. 41 (2001) 1208–1217 Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 26 Strategies to Improve Solubility:

Example A R1 R1 R1 N N N N N N N R2 Rauthor2 R2

R4 R3 R4 R3 R4 R3

by O N N N

F F

Property Cpd A Cpd B Cpd C solubility of neutral [mM] 0.01 0.02 0.10 solubility @pH6.8 [mM] 0.01eLibrary 0.02 0.10 fraction ionized @pH6.8 0.0 0.0 0.0 logP 3.5 3.1 3.1

melting point Tm 189ºC 157ºC 111ºC

 Decrease inESCMID logP and melting point improves solubility  Trends may© be envisioned qualitatively, not quantitatively Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 27 Strategies to Improve Solubility: Example B

R R R N N authorN NH NH NH Cl by O O N N R2 OH

Property Cpd A Cpd B Cpd C solubility of neutral [mM] 0.001 0.002 0.25 solubility @pH6.8 [mM] 0.001eLibrary 0.21 0.25 fraction ionized @pH6.8 0.0 1.0 0.0 logP 4.5 3.8 3.2

melting point Tm 187ºC 225ºC 158ºC

 Properties ESCMIDare interconnected  Structural© changes affect one or multiple properties Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 28 Agenda

• Introduction “Drug-Likeness” author & Properties by

• Ionization • Lipophilicity • SolubilityeLibrary

• Summary & Conclusion ESCMID ©

28 What is the “Best” PhysChem Target Property Profile? Oral

Anti-author IV biotics injection by

Target Property Profile

Topical eLibrary Intra- ocular

into brain  Desired targetESCMID property profile depends also on route of administration© and target location Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 30 Summary & Conclusion

• A successful drug needs high potency/activity AND good properties author • PK & physchem properties should beby considered early on, e.g.

• Ionization • LipophilicityeLibrary • Solubility

• Desired target property profile depends also on route of administrationESCMID and target location © Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 31 30 author by

eLibrary Thank you!

32 author

Andrea Decker, Ph.D. by Fellow, Chemical and Pharmaceutical Profiling

Novartis Global Drug Development Technical Research & Development CH-4002 Basel Switzerland +41 79 831 00 97 eLibrary [email protected]

34 Literature references

• Benet, L. Z., et al. (2016). "BDDCS, the Rule of 5 and drugability." Adv Drug Deliv Rev. • Broccatelli, F., et al. (2018). "Why Decreasing Lipophilicity Alone Is Often Not a Reliable Strategy for Extending IV Half-life." ACS Medicinal Chemistry Letters 9(6): 522-527. • Cavalluzzi, M. M., et al. (2017). "Ligand efficiency metrics in drug discovery: the pros and cons fromauthor a practical perspective." Expert Opinion on Drug Discovery 12(11): 1087-1104. • Charifson, P. S. and W. P. Walters (2014). "Acidic and Basic Drugs in Medicinal Chemistry: A Perspective." J Med Chem 57(23): 9701- 9717. by • Daina, A., et al. (2017). "SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules." Sci Rep 7: 42717. • Eder, J., et al. (2014). "The discovery of first-in-class drugs: origins and evolution." Nat Rev Drug Discov 13(8): 577-587. • Faller, B. and P. Ertl (2007). "Computational approaches to determine drug solubility." Adv Drug Deliv Rev 59(7): 533-545. • Gleeson, M. P., et al. (2011). "Probing the links between in vitro potency, ADMET and physicochemical parameters." Nat Rev Drug Discov 10(3): 197-208. • Gunaydin, H., et al. (2018). "Strategy for Extending Half-life in Drug Design and Its Significance." ACS Medicinal Chemistry Letters 9(6): 528-533. • Harrison, R. K. (2016). "Phase II and phase III failures: 2013eLibrary-2015." Nat Rev Drug Discov 15(12): 817-818. • Hill, A. P. and R. J. Young (2010). "Getting physical in drug discovery: a contemporary perspective on solubility and hydrophobicity." Drug Discov Today 15(15–16): 648-655. • Hopkins, A. L., et al. (2014). "The role of ligand efficiency metrics in drug discovery." Nat Rev Drug Discov 13(2): 105-121. • Kola, I. and J. Landis (2004). "Can the pharmaceutical industry reduce attrition rates?" Nat Rev Drug Discov 3(8): 711-716. • Kramer, C., et al. (2018). "Learning Medicinal Chemistry Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) Rules from Cross-Company Matched Molecular Pairs Analysis (MMPA)." J Med Chem 61(8): 3277-3292. • Leeson, P. D. (2016). "Molecular inflation, attrition and the rule of five." Adv Drug Deliv Rev. • Leeson, P. D. (2018). "Impact of Physicochemical Properties on Dose and Hepatotoxicity of Oral Drugs." Chem Res Toxicol. • Leeson, P. D., et al. (2011).ESCMID "Impact of ion class and time on oral drug molecular properties." Med. Chem. Commun. 2(2): 91-105. • Lipinski, C. A. (2016). "Rule of five in 2015 and beyond: Target and ligand structural limitations, ligand chemistry structure and drug discovery project decisions."© Adv Drug Deliv Rev. Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 35 Literature references

• Lipinski, C. A., et al. (2012). "Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings." Adv Drug Deliv Rev 64: 4-17. • Lovering, F., et al. (2009). "Escape from flatland: increasing saturation as an approach to improving clinical success." J Med Chem 52(21): 6752-6756. author • Manallack, D. T., et al. (2013). "The significance of acid/base properties in drug discovery." Chem Soc Rev 42(2): 485-496. • Manallack, D. T., et al. (2018). "The influence and manipulation of acid/base properties in drug discovery." Drug Discovery Today: Technologies. by • Meanwell, N. A. (2011). "Improving drug candidates by design: a focus on physicochemical properties as a means of improving compound disposition and safety." Chem Res Toxicol 24(9): 1420-1456. • Meanwell, N. A. (2016). "Improving Drug Design: An Update on Recent Applications of Efficiency Metrics, Strategies for Replacing Problematic Elements, and Compounds in Nontraditional Drug Space." Chem Res Toxicol 29(4): 564-616. • Mignani, S., et al. (2018). "Present drug-likeness filters in medicinal chemistry during the hit and lead optimization process: how far can they be simplified?" Drug Discov Today 23(3): 605-615. • Ran, Y., et al. (2001). "Prediction of Aqueous Solubility of Organic Compounds by the General Solubility Equation (GSE)." Journal of Chemical Information and Computer Sciences 41(5): 1208-1217. • Shultz, M. D. (2014). "Improving the plausibility of successeLibrary with inefficient metrics." ACS Med Chem Lett 5(1): 2-5. • Tsopelas, F., et al. (2017). "Lipophilicity and biomimetic properties to support drug discovery." Expert Opin Drug Discov: 1-12. • Vistoli, G., et al. (2008). "Assessing drug-likeness--what are we missing?" Drug Discov Today 13(7-8): 285-294. • Ward, S. E. and P. Beswick (2014). "What does the aromatic ring number mean for drug design?" Expert Opin Drug Discov 9(9): 995-1003. • Waring, M. J., et al. (2015). "An analysis of the attrition of drug candidates from four major pharmaceutical companies." Nat Rev Drug Discov 14(7): 475-486. • Wohnsland, F. and B. Faller (2001). "High-Throughput Permeability pH Profile and High-Throughput Alkane/Water log P with Artificial Membranes." J Med Chem 44(6): 923-930. • Wong, H., et al. (2017). "Translational pharmacokinetic-pharmacodynamic analysis in the pharmaceutical industry: an IQ Consortium PK-PD Discussion Group perspective."ESCMID Drug Discov Today. • Young, R. J., et al. (2011). "Getting physical in drug discovery II: the impact of chromatographic hydrophobicity measurements and aromaticity." Drug Discov© Today 16(17-18): 822-830. Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 36 Overview of Novartis Drug Discovery and Development Pathway

Targets & pathways • iterative • dynamicauthor Exploratory • responsive • bymultidimensional

Clinical Clinical Readiness Evaluation Assays & compounds Candidates

Iterative Discovery process CharacterizationeLibrary Preclinical Clinical

Leads

Optimization ESCMID © Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 37 Ampholytes and Zwitterions

+ HO HO XH O - 100.0 2 XH X + - XH2 XH X 80.0 O H O H O H 60.0 N N N author H+ 40.0 HO HO HO 20.0by Morphine: pKa’s : B (8.2) – A (9.3) 0.0 Distribution of of (%) species Distribution 1.0 3.0 5.0 7.0 9.0 11.0 Ampholyte: "neutral" form exists at IEP pH (concentration scale) without formal charges IEP: Isoelectric point

+ ± - ZH2 ZH Z eLibrary 100.0 + ± + + ZH2 ZH H2N H N HN 80.0 2 - N N N N N N Z 60.0 O O F F O F - 40.0 OH - O O O O O 20.0

0.0 Ciprofloxacin: pKa’s : A (6.2) – B (8.6) of (%) species Distribution 1.0 3.0 5.0 7.0 9.0 11.0 ESCMID pH (concentration scale) Zwitterion: pseudo neutral form at IEP (pH=7.4)  simultaneously©+ & - charged Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 38 logP: The Fundamentals Logarithmic Scale author by

Acetazolamide Trichlormethiazide Chlorzoxazone Lasofoxifene logP = -0.12 logP = 0.97 logP = 2.1 logP = 5.84

logP = 0 logP = 1 eLibrarylogP = 2 logP = 6

= 10 = 1 = 10 = 10 = 10 = 100 = 10 = 1 𝒐𝒐𝒐𝒐𝒐𝒐 𝒐𝒐𝒐𝒐𝒐𝒐 𝑿𝑿𝒐𝒐𝒐𝒐𝒐𝒐 0 𝑿𝑿 1 𝑿𝑿 2 𝑿𝑿𝒐𝒐𝒐𝒐𝒐𝒐 6 ′ = 𝒘𝒘 = 𝒘𝒘 = = 000′000 𝑿𝑿𝒘𝒘 𝑿𝑿 𝑿𝑿 𝑿𝑿𝒘𝒘 𝟔𝟔 𝑜𝑜𝑜𝑜𝑜𝑜 𝑤𝑤 𝑜𝑜𝑜𝑜𝑜𝑜 𝑤𝑤 𝑜𝑜𝑜𝑜𝑜𝑜 𝑤𝑤 𝑋𝑋 𝑋𝑋 𝑋𝑋 𝟏𝟏𝟏𝟏 ∗ 𝑋𝑋 𝑋𝑋 𝟏𝟏𝟏𝟏𝟏𝟏 ∗ 𝑋𝑋 𝑋𝑋𝑜𝑜𝑜𝑜𝑜𝑜 𝟏𝟏𝟏𝟏 ∗ 𝑋𝑋𝑤𝑤 ESCMID © Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 39 pKa measurement: Instrumentation

Capillaries, for adding reagents UV Dip Probe.author by

Glass vial,

Sirius Analytical Ltd. http://www.sirius-analytical.com 4 ml total eLibrary capacity • Automated titrator Automatic overhead – UV-base titration Stirrer – Potentiometric titration Electronic thermometer pH electrode, • More than just pKa determination diameter 3mm (logP, Intrinsic solubility,ESCMID Supersaturation© ratio, pHmax...) Sirius Analytical Ltd. http://www.sirius-analytical.com Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 40 LogD: pH Dependence Acids (AH) author by

eLibrary

ESCMID logD ≤ logP© (always!) Curr Drug Metab.; 2008 Nov; 9(9):869-78 Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 41 LogD: pH Dependence Bases (B) author by

eLibrary

ESCMID logD ≤ logP© (always!) Curr Drug Metab.; 2008 Nov; 9(9):869-78 Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 42 Lipophilicity: How it can be predicted • Many commercial software packages: – clogP (BioByte): tried and tested, based on oldauthor data – Moka, ACD-labs, ADMET predictor, ChemDrawby , COSMO-RS, ...

• Internal model: – NIBR:logP: machine learning model, trained on internal and external data (>15k cpd’s) eLibrary P Gedeck, et al.; unpublished data

Easy to calculate Easy to measure logP vs. logD Difficult to measureESCMID Difficult to calculate © Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 43 clogP (BioByte) Comparison to Experimental logP

Difference author by

eLibrary predicted Biobyte clogP • no qualified values • ~3700 data points

experimental logP  Relatively largeESCMID error  Not very© reliable prediction (project dependent) Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 44 clogP (Biobyte) vs. NIBR:logP Comparison to Experimental logP author by

9 %9 % 13 %13 %

33 %33 %

40 %40 %%40 23 %23 % eLibrary20 %20 %%20 predicted NIBR:logP predicted Biobyte clogP

27 %27 %%27 35 %35 %

experimental logP experimental logP ESCMID  Highly improved© performance compared to clogP Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 45 Solubility: How it can be predicted

• In-silico prediction of solubility VERY DIFFICULT author • Many approaches and methods – Fitted equations or estimates; by e.g. “General Solubility Equation”:

Yalkowsky et al.; 1980 J. Pharm. Sci. 69(8): 912-922. Jain et al.; 2001 J. Pharm. Sci 90(2): 234eLibrary-252. – Physics-based models – Machine -learning models

 State-of-the-art: ESCMID From Skyner, R. E., et al. (2015). Phys 0.7-1.0 ©log unit (i.e. x10) accuracy Chem Chem Phys 17(9): 6174-6191. Drug Likeness: PhysChem Properties / Andrea Decker / Lisbon, September 2018 46