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Better (Combinatorial) Screening through PhysChem

Learn how physical properties impact drug absorption and activity in research, and how optimizing them simultaneously can enhance screening outcomes. Discover opportunities for better screening using experimental design, combinatorial libraries, compound pooling, and screening conditions.

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Better (Combinatorial) Screening through PhysChem

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  1. Better (Combinatorial) ScreeningthroughPhysChem Robert S DeWitte, PhD Advanced Chemistry Development Inc. Toronto Ontario Canada

  2. Advanced Chemistry Development

  3. Why do Physical Properties create opportunity? • Absorption and Activity are two central themes in Drug Discovery Research • Absorption relates the ability of a potential drug to enter the blood stream after administration • Driven by solubility and lipophilicity • Activity relates the ability of a potential drug to elicit the desired effect once it reaches the site of action • Driven by hydrogen bonds and hydrophobic effect • These often come one at the expense of the other, so simultaneously optimizing both is difficult • Experimental Design

  4. Absorption • Poor Physical Properties account for more than half of the failures of drug candidates • Over 50% of Drug Candidates are rejected due to poor pharmacokinetic properties • Almost 30% of failures occur during development • Too Late for Chemistry • Formulation • An expensive option • Not always able to rescue a difficult agent

  5. Absorption • Many compounds of biological interest are not neutral • Hydrophobicity (LogD) is pH dependent • Solubility is pH dependent • Presentation from Pfizer this week at AAPS • Absorption = Solubility X Permeability • Permeability varies 40 fold • Solubility varies 1,000,000 fold • Therefore solubility is key

  6. physiology & biophysics of GI tract 120 m2 0.3 m2 3-4 hr 0.5-3.5 hr bases 0.1 m2 1 - 3 d acids Stomach 1.4-2.1 3 - 7 Jejunum 4.4 - 6.6 5.2 - 6.2 Ileum 6.8 - 8.0 6.8 - 8.0 Colon 5 - 8 5 - 8 fasted state pH fed state Dressman, Amidon, Reppas, Shah, Pharm. Res. 1998, 15, 11.

  7. Lipophilicity is pH dependent LogP is not Enough!

  8. Solubility is pH dependent Only ACD predicts solubility as a function of pH!

  9. Experimental Design • Combinatorial Libraries • Early Combinatorial Chemistry was aimed at large mix-and-split libraries • Most compounds were too greasy for screening • Recently, targeted parallel synthesis has become popular • Smaller focused libraries provide the opportunity for more careful screening • Opportunities for better screening • Compound Pooling • Library Design • Screening Conditions

  10. Opportunities for better screening • Compound Pooling • Compounds can be grouped according to their properties • Like with like for similar physical sample characteristics • pKa’s of ionizable centres to present samples as neutral forms • Solubility to select a suitable target concentration • Maximally Diverse for easier hit identification • Molecular Weight (MS) • LogD (HPLC)

  11. Opportunities for better screening • Library Design • The Space of Physical Properties can be sampled with maximal diversity • Broadest possible range of LogD, pKa values to generate the most information • Targeted ranges • Keep Solubility in range, vary LogD systematically, keep pKa near 9.6 • Size compensation • Vary the size of substituents without affecting LogD

  12. Opportunities for better screening • Screening Conditions • If compound pooling has been done, you can • Vary pH to systematically affect LogD • Vary pH to assure that the neutral form (or +ve ion form) is presented to the target • Vary the dilution of the target to compensate for solubility effects • Even without compound pooling, reference to the distribution of Physical Properties in the library will inform the conditions or interpretation of results

  13. Modes of Application • Virtual Screening • At design time • ADME Screening • Pool compounds to simplify setting experimental conditions • e.g: for optimal HPLC retention times • HTS Screening • Pool compounds to systematize the variation among observations, quenching significant noise, providing enhanced signal-to-noise ratio

  14. User Training and Libraries • At the time that combinatorial library is being planned • Typically, at least one related lead compound is known • Select minimalist related lead compound for experimental measurement • Use measurement for user training • Enumerate combi-library • Predict Physical properties • Prune Library • Pool Compounds • Establish Screening Conditions

  15. User Training System

  16. Summary • Physical properties provide insight into absorption, activity and experimental design • Trends that reduce the size of combinatorial libraries provide the opportunity to reduce noise in screening by using ACD/PhysChem to • Pool compounds • Design libraries • Select screening conditions • User training in conjunction with PhysChem Batch provides an accurate route to Physical Property Prediction for Combi-chem applications

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