Amorphous Blobs of Hope and Other Flights of Fancy. Steve Muchmore Chemaxon UGM April 18, 2011 Budapest
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1 Amorphous Blobs of Hope and Other Flights of Fancy Steve Muchmore Chemaxon UGM April 18, 2011 Budapest
2 Rules of Thumb help folks make objective and informed decisions in the face of incomplete or inaccurate information. typically consist of information distilled down to minimum as a mnemonic (ie, the width of a carpenter s thumb is approximately 1 inch) and in today s usage, term implies an imprecise but generally reliable and convenient standard 2
3 Rules of Thumb RO5 Proposed by Lipinksy, etal in 1997 (Pfizer) Orally bioavailabe compounds should have only one violation of the following molecular properties: Molecular weight less than 500 logp less than 5 Hydrogen bond donors less than 5 Total number of nitrogen and oxygen atoms less than 10 - Have been implemented in many tools - Generally considered harmless - How Predictive? 3
4 Golden Triangle Published by Johnson, et al 2009 (Pfizer) Derived by analysis of PAMPA and HLM % remaining data Suggests that compounds with best oral absorbance and optimal clearance found in golden triangle Subset of ROF (MW lt 500 and logp lt 5 4
5 3/75 Rule Published by Hughes, etal 2008 (Pfizer) Suggests that compounds with compounds with logp greater than three and tpsa less than 75, that you have a 2.5 times greater chance at being toxic Assumed to be due to the compounds promiscuity as measured by CEREP panel data 5
6 Solubility and General Developability Lovering, 2009 (Wyeth) and Ritchie, 2009, GSK CLND solubility affected by two chemical features fsp3 less than 0.4 leads to poor solubility Number of Aromatic Rings gt 3 leads to poor solubility and formulation problems. 6
7 So, What s The Problem? Unnecessary reduction in information content Potentially leads to miss-application and mis-understanding of the intent of the rule of thumb Lipinsky deliberately emphasized enhanced educational effectiveness towards a well defined target audience at the expense of a loss of detail. - Hard cutoffs in properties lead to discontinuities Does a compound with a MW of 501 really have that different of a property than one that has a MW of 499? tpsa of 74 different from 76? - Is this a problem that we ve oversimplified? Do we need to take a harder look at the data? 7
8 If Not Rules of Thumb, Then What? Ideally like to have visualization and ranking tools that: Are easy to interpret and remember Are generally applicable Information rich, heavily influenced by experimental results Don t suffer from artificial data discontinuities (arbitrary cut-offs) - Various ways to achieve goal: Rules of Thumb Hit to Lead tiering system Aloha (Derek Debe) PABOH visualization (this work) 8
9 What Do The Data Tell Us? What data do we have to examine whether or not these rules of thumb are useful? How well do the rules explain those data? Solubility: ~10,000 CLND data pts, ph 7.4 PAMPA: ~6000 measurements HLM: ~5500 measurements CEREP data ~10000 data pts from 75 different targets 9
10 PABOH?? What the heck? In the following plots, we illustrate the trends in our in-house data by plotting the probability of a positive result vs. two molecular properties The probability of positive result is defined as the ratio to good vs. bad results in each of the data bin. Each data bin required to have 5 or more measurements Plot smoothing was done same function often used in generating weather isobars PABOH: Polychromatic Amorphous Blobs of Hope 10
11 PABOH with PAMPA Data Probability of exhibiting PAMPA > 2.5 x 10 6 cm/sec measurement MW vs. calculated logd Green is highest probability Abbott in-house data 11
12 PABOH with HLM Data MW vs. LogD Probability of 40% remaining in Human Liver Microsome tests from HT-ADME 12
13 Combined HLM and PAMPA Since PABOH plots are probabilities of success, if they are calculated using similar axes, they can be combined This plot is simple sum of HLM and PAMPA PABOH plots Equivalent to Golden Triangle or RO5 property space 13
14 PABOH vs. Golden Triangle 14
15 PABOH vs. RO5 15
16 Comparison of Combined HLM and PAMPA to Rat PO How well does PABOH for combined HLM and PAMPA data predict bioavailability? 16
17 # Aromatic Rings Probability of CLND >=10 um PABOH Plots for Solubility fsp3 17
18 # Aromatic Rings PABOH Plots vs. nar < 3, fsp3 > 0.4 fsp3 18
19 tpsa < 10 % CEREP > 30% Inhibition PABOH Toxicity/Promiscuity ClogP 19
20 tpsa < 10 % CEREP > 30% Inhibition PABOH vs. 3/75 rule ClogP 20
21 Orally Administered Drugs 117 orally available, marketed drugs Guess which two are Abbott Drugs? 21
22 Conclusions Simple rules of thumb are of limited use in careful data analysis - Discontinuities in cutoffs - Innaccurate representation of data Large amounts of data are available in corporate collections to allow more detailed analyses Continuous functions that describe trends in data can be useful Probability space allows for combination of data from disparate sources 22
23 Acknowledgments Cheminformatics - James Metz - Scott Brown - Isabella Haight - Yvonne Martin Visiting Scientist - Rob Gregg Discovery IT - Ravindra Mamidipaka - Derek Debe Advanced Technology - Phil Hajduk - Alfred Hahn ADME/Tox - Cory Kalvass - Richard Voorman - Mira Hinman - Kelly Desino 23
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