Affordable Access

BDDCS Class Prediction for New Molecular Entities

American Chemical Society
Publication Date
  • The Biopharmaceutics Drug Disposition Classification System (Bddcs) Was Successfully Employed For Pr
  • Drug Transporters And Their Interplay
  • The Major Assumption Of Bddcs Is That The Extent Of Metabolism (Eom) Predicts High Versus Low Intest
  • And Vice Versa
  • At Least When Uptake Transporters Or Paracellular Transport Is Not Involved
  • We Recently Published A Collection Of Over 900 Marketed Drugs Classified For Bddcs
  • We Suggest That A Reliable Model For Predicting Bddcs Class
  • Integrated With In Vitro Assays
  • Could Anticipate Disposition And Potential Ddis Of New Molecular Entities (Nmes)
  • Here We Describe A Computational Procedure For Predicting Bddcs Class From Molecular Structures
  • The Model Was Trained On A Set Of 300 Oral Drugs
  • And Validated On An External Set Of 379 Oral Drugs
  • Using 17 Descriptors Calculated Or Derived From The Volsurf+ Software
  • For Each Molecule
  • A Probability Of Bddcs Class Membership Was Given
  • Based On Predicted Eom
  • Fda Solubility (Fdas) And Their Confidence Scores
  • The Accuracy In Predicting Fdas Was 78% In Training And 77% In Validation
  • While For Eom Prediction The Accuracy Was 82% In Training And 79% In External Validation
  • The Actual Bddcs Class Corresponded To The Highest Ranked Calculated Class For 55% Of The Validation
  • And It Was Within The Top Two Ranked More Than 92% Of The Time
  • The Unbalanced Stratification Of The Data Set Did Not Affect The Prediction
  • Which Showed Highest Accuracy In Predicting Classes 2 And 3 With Respect To The Most Populated Class
  • For Class 4 Drugs A General Lack Of Predictability Was Observed
  • A Linear Discriminant Analysis (Lda) Confirming The Degree Of Accuracy For The Prediction Of The Dif
  • This Model Could Routinely Be Used In Early Drug Discovery To Prioritize In Vitro Tests For Nmes (E
  • G
  • Affinity To Transporters
  • Intestinal Metabolism
  • Intestinal Absorption Andplasma Protein Binding)
  • We Further Applied The Bddcs Prediction Model On A Large Set Of Medicinal Chemistry Compounds (Over
  • 000 Chemicals)
  • Based On This Application
  • We Suggest That Solubility
  • And Not Permeability
  • Is The Major Difference Between Nmes And Drugs
  • We Anticipate That The Forecast Of Bddcs Categories In Early Drug Discovery May Lead To A Significan
  • D Cost Reduction


BDDCS Class Prediction for New Molecular Entities - DTU Orbit (18/06/14) BDDCS Class Prediction for New Molecular Entities - DTU Orbit (18/06/14) BDDCS Class Prediction for New Molecular Entities. / Broccatelli, Fabio; Cruciani, Gabriele; Benet, Leslie Z.; Oprea, Tudor. In: Molecular Pharmaceutics, Vol. 9, No. 3, 2012, p. 570-580. Publication: Research - peer-review › Journal article – Annual report year: 2012

There are no comments yet on this publication. Be the first to share your thoughts.