Screening oral drugs for their interactions with the intestinal transportome via porcine tissue explants and machine learning.

Journal: Nature biomedical engineering
Published Date: Feb 20, 2024

Abstract

In vitro systems that accurately model in vivo conditions in the gastrointestinal tract may aid the development of oral drugs with greater bioavailability. Here we show that the interaction profiles between drugs and intestinal drug transporters can be obtained by modulating transporter expression in intact porcine tissue explants via the ultrasound-mediated delivery of small interfering RNAs and that the interaction profiles can be classified via a random forest model trained on the drug-transporter relationships. For 24 drugs with well-characterized drug-transporter interactions, the model achieved 100% concordance. For 28 clinical drugs and 22 investigational drugs, the model identified 58 unknown drug-transporter interactions, 7 of which (out of 8 tested) corresponded to drug-pharmacokinetic measurements in mice. We also validated the model's predictions for interactions between doxycycline and four drugs (warfarin, tacrolimus, digoxin and levetiracetam) through an ex vivo perfusion assay and the analysis of pharmacologic data from patients. Screening drugs for their interactions with the intestinal transportome via tissue explants and machine learning may help to expedite drug development and the evaluation of drug safety.

Authors

  • Yunhua Shi
    David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Daniel Reker
    Swiss Federal Institute of Technology (ETH), Department of Chemistry and Applied Biosciences, Vladimir-Prelog-Weg 4, 8093 Zürich, Switzerland.
  • James D Byrne
    Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Ameya R Kirtane
    David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Kaitlyn Hess
    David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
  • Zhuyi Wang
    Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Natsuda Navamajiti
    Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Cameron C Young
    Harvard Medical School, Boston, MA, USA.
  • Zachary Fralish
    Department of Biomedical Engineering, Duke University, Durham, NC, USA.
  • Zilu Zhang
    College of Chemistry and Materials Science, Guangdong Provincial Key Laboratory of Functional Supramolecular Coordination Materials and Applications, Guangdong Engineering & Technology Research Centre of Graphene-like Materials and Products, Jinan University, Guangzhou 510632, China.
  • Aaron Lopes
    Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Vance Soares
    Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Jacob Wainer
    Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Thomas von Erlach
    Department of Chemical Engineering and Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Lei Miao
    School of Computer Science and Engineering, Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing 210096, China. Electronic address: miaolei@seu.edu.cn.
  • Robert Langer
    Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.
  • Giovanni Traverso
    David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Division of Gastroenterology, Hepatology and Endoscopy, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; MIT-IBM Watson AI Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Electronic address: cgt20@mit.edu.

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