안녕하세요? 퀀텀바이오솔루션즈입니다.
SLP 소프트웨어와 관련하여 새롭게 업데이트된 논문을 소개드립니다.
Characterization of preclinical radio ADME properties of ARV-471 for predicting human PK using PBPK modeling.
He Y, Zhu C, Lei P, Yang C, Zhang Y, Zheng Y, Diao X. (2024) J. Pharm. Analysis Dec. 28
Keywords: gastroplus, pbpk modeling, physiologically based pharmacokinetics, pbbm, protac, food effect, ivive, fih, first in human
Phase I clinical trial of NH130 and the prediction of its pharmacokinetics using physiologically based pharmacokinetic modeling.
Zhang K, Zhao S, Du J, Zhang L. (2024) Front Pharmacol. Sep 12;15:1474868
Keywords: gastroplus, pbpk modeling, physiologically based pharmacokinetics, pbbm, fih, first in human, dose selection, phase I
Physiologically based pharmacokinetic modeling for confirming the role of CYP3A1/2 and P-glycoprotein in detoxification mechanism between glycyrrhizic acid and aconitine in rats.
Jin J, Xu X, Li F, Weng F, Zou B, Li Y, Zhao J, Zhang S, Yan D, Qiu F. (2024) J Appl Toxicol. Jul;44(7):978-989
Keywords: gastroplus, pbpk modeling, physiologically based pharmacokinetics, pbbm, nonlinear pk, cyp 3a1/2, p-gp, transporters
Accurate prediction of Kp,uu,brain based on experimental measurement of Kp,brain and computed physicochemical properties of candidate compounds in CNS drug discovery.
Ma Y, Jiang M, Javeria H, Tian D, Du Z. (2024) Heliyon. Jan 9;10(2):e24304
Keywords: admet predictor, machine learning, adme prediction, virtual screening, qsar, admet risk, lead selection, neuroscience, brain penetration
Drug-like properties of serial phenanthroindolizidine alkaloid compounds: ADMET characteristic prediction and validation.
Wang H, Hu J, Ji M, Wang R, Jin J, Ye J, Zhang H, Li L, Wang R, Yang Y, Gao Y, Xia X, Xu X, Gao L, Liu Y. (2024) Acta Materia Medica. Vol. 3(1):88-104
Keywords: admet predictor, machine learning, adme prediction, virtual screening, qsar, admet risk, lead selection
주소 : 서울특별시 강남구 역삼로112 하나빌딩 301호
안녕하세요? 퀀텀바이오솔루션즈입니다.
SLP 소프트웨어와 관련하여 새롭게 업데이트된 논문을 소개드립니다.
Characterization of preclinical radio ADME properties of ARV-471 for predicting human PK using PBPK modeling.
He Y, Zhu C, Lei P, Yang C, Zhang Y, Zheng Y, Diao X. (2024) J. Pharm. Analysis Dec. 28
Keywords: gastroplus, pbpk modeling, physiologically based pharmacokinetics, pbbm, protac, food effect, ivive, fih, first in human
Phase I clinical trial of NH130 and the prediction of its pharmacokinetics using physiologically based pharmacokinetic modeling.
Zhang K, Zhao S, Du J, Zhang L. (2024) Front Pharmacol. Sep 12;15:1474868
Keywords: gastroplus, pbpk modeling, physiologically based pharmacokinetics, pbbm, fih, first in human, dose selection, phase I
Physiologically based pharmacokinetic modeling for confirming the role of CYP3A1/2 and P-glycoprotein in detoxification mechanism between glycyrrhizic acid and aconitine in rats.
Jin J, Xu X, Li F, Weng F, Zou B, Li Y, Zhao J, Zhang S, Yan D, Qiu F. (2024) J Appl Toxicol. Jul;44(7):978-989
Keywords: gastroplus, pbpk modeling, physiologically based pharmacokinetics, pbbm, nonlinear pk, cyp 3a1/2, p-gp, transporters
Accurate prediction of Kp,uu,brain based on experimental measurement of Kp,brain and computed physicochemical properties of candidate compounds in CNS drug discovery.
Ma Y, Jiang M, Javeria H, Tian D, Du Z. (2024) Heliyon. Jan 9;10(2):e24304
Keywords: admet predictor, machine learning, adme prediction, virtual screening, qsar, admet risk, lead selection, neuroscience, brain penetration
Drug-like properties of serial phenanthroindolizidine alkaloid compounds: ADMET characteristic prediction and validation.
Wang H, Hu J, Ji M, Wang R, Jin J, Ye J, Zhang H, Li L, Wang R, Yang Y, Gao Y, Xia X, Xu X, Gao L, Liu Y. (2024) Acta Materia Medica. Vol. 3(1):88-104
Keywords: admet predictor, machine learning, adme prediction, virtual screening, qsar, admet risk, lead selection