BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

174 related articles for article (PubMed ID: 34758626)

  • 1. Machine Learning Models for Human
    Miljković F; Martinsson A; Obrezanova O; Williamson B; Johnson M; Sykes A; Bender A; Greene N
    Mol Pharm; 2021 Dec; 18(12):4520-4530. PubMed ID: 34758626
    [TBL] [Abstract][Full Text] [Related]  

  • 2. In Silico Prediction of Human Intravenous Pharmacokinetic Parameters with Improved Accuracy.
    Wang Y; Liu H; Fan Y; Chen X; Yang Y; Zhu L; Zhao J; Chen Y; Zhang Y
    J Chem Inf Model; 2019 Sep; 59(9):3968-3980. PubMed ID: 31403793
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Comparing the applications of machine learning, PBPK, and population pharmacokinetic models in pharmacokinetic drug-drug interaction prediction.
    Gill J; Moullet M; Martinsson A; Miljković F; Williamson B; Arends RH; Pilla Reddy V
    CPT Pharmacometrics Syst Pharmacol; 2022 Dec; 11(12):1560-1568. PubMed ID: 36176050
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Prediction of In Vivo Pharmacokinetic Parameters and Time-Exposure Curves in Rats Using Machine Learning from the Chemical Structure.
    Obrezanova O; Martinsson A; Whitehead T; Mahmoud S; Bender A; Miljković F; Grabowski P; Irwin B; Oprisiu I; Conduit G; Segall M; Smith GF; Williamson B; Winiwarter S; Greene N
    Mol Pharm; 2022 May; 19(5):1488-1504. PubMed ID: 35412314
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Direct Comparison of Total Clearance Prediction: Computational Machine Learning Model versus Bottom-Up Approach Using In Vitro Assay.
    Kosugi Y; Hosea N
    Mol Pharm; 2020 Jul; 17(7):2299-2309. PubMed ID: 32478525
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Advances in Predictions of Oral Bioavailability of Candidate Drugs in Man with New Machine Learning Methodology.
    Fagerholm U; Hellberg S; Spjuth O
    Molecules; 2021 Apr; 26(9):. PubMed ID: 33925103
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Quantitative structure-activity relationship models of clinical pharmacokinetics: clearance and volume of distribution.
    Gombar VK; Hall SD
    J Chem Inf Model; 2013 Apr; 53(4):948-57. PubMed ID: 23451981
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Another string to your bow: machine learning prediction of the pharmacokinetic properties of small molecules.
    Bassani D; Parrott NJ; Manevski N; Zhang JD
    Expert Opin Drug Discov; 2024 Jun; 19(6):683-698. PubMed ID: 38727016
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Predictive Modelling in pharmacokinetics: from in-silico simulations to personalized medicine.
    Paliwal A; Jain S; Kumar S; Wal P; Khandai M; Khandige PS; Sadananda V; Anwer MK; Gulati M; Behl T; Srivastava S
    Expert Opin Drug Metab Toxicol; 2024 Apr; 20(4):181-195. PubMed ID: 38480460
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Predicting drug metabolism and pharmacokinetics features of in-house compounds by a hybrid machine-learning model.
    Sasahara K; Shibata M; Sasabe H; Suzuki T; Takeuchi K; Umehara K; Kashiyama E
    Drug Metab Pharmacokinet; 2021 Aug; 39():100395. PubMed ID: 33991751
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Preclinical pharmacokinetics: an approach towards safer and efficacious drugs.
    Singh SS
    Curr Drug Metab; 2006 Feb; 7(2):165-82. PubMed ID: 16472106
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Systematic Evaluation of Local and Global Machine Learning Models for the Prediction of ADME Properties.
    Di Lascio E; Gerebtzoff G; Rodríguez-Pérez R
    Mol Pharm; 2023 Mar; 20(3):1758-1767. PubMed ID: 36745394
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Application of machine learning techniques in population pharmacokinetics/pharmacodynamics modeling.
    Uno M; Nakamaru Y; Yamashita F
    Drug Metab Pharmacokinet; 2024 Jun; 56():101004. PubMed ID: 38795660
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Evaluating the performance of machine-learning regression models for pharmacokinetic drug-drug interactions.
    Gill J; Moullet M; Martinsson A; Miljković F; Williamson B; Arends RH; Pilla Reddy V
    CPT Pharmacometrics Syst Pharmacol; 2023 Jan; 12(1):122-134. PubMed ID: 36382697
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Evaluation of Generic Methods to Predict Human Pharmacokinetics Using Physiologically Based Pharmacokinetic Model for Early Drug Discovery of Tyrosine Kinase Inhibitors.
    Ren HC; Sai Y; Chen T
    Eur J Drug Metab Pharmacokinet; 2019 Feb; 44(1):121-132. PubMed ID: 30039459
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Application of Machine Learning Technology in the Prediction of ADME- Related Pharmacokinetic Parameters.
    Wang Y; Zhan Y; Liu C; Zhan W
    Curr Med Chem; 2023; 30(17):1945-1962. PubMed ID: 35993465
    [TBL] [Abstract][Full Text] [Related]  

  • 17.
    Fagerholm U; Hellberg S; Alvarsson J; Spjuth O
    Altern Lab Anim; 2023 Jan; 51(1):39-54. PubMed ID: 36572567
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Feature importance of machine learning prediction models shows structurally active part and important physicochemical features in drug design.
    Sasahara K; Shibata M; Sasabe H; Suzuki T; Takeuchi K; Umehara K; Kashiyama E
    Drug Metab Pharmacokinet; 2021 Aug; 39():100401. PubMed ID: 34089983
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Prediction of Oral Pharmacokinetics Using a Combination of In Silico Descriptors and In Vitro ADME Properties.
    Kosugi Y; Hosea N
    Mol Pharm; 2021 Mar; 18(3):1071-1079. PubMed ID: 33512165
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Prediction of Compound Plasma Concentration-Time Profiles in Mice Using Random Forest.
    Handa K; Wright P; Yoshimura S; Kageyama M; Iijima T; Bender A
    Mol Pharm; 2023 Jun; 20(6):3060-3072. PubMed ID: 37096989
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.