A systems biology based integrative framework to enhance the predictivity of in vitro methods for drug-induced liver injury.
BACKGROUND
Liver injury is the most common cause of postmarketing withdrawal of drugs. Traditional animal toxicity testing methods have proved to be imperfect tools for predicting toxicity observed in the clinic.


OBJECTIVE
Predictive methods that integrate data and insights from several in vitro methods to provide a deeper understanding of the impact of a drug on the liver are the need of the hour.


METHODS
A systems approach based on mathematical modelling using the kinetics of biochemical pathways involved in liver homeostasis coupled with in vitro measurements to quantify drug-induced perturbations is described here.


CONCLUSIONS
Integrating in silico and in vitro methods provides a powerful platform that allows reasonably accurate and mechanistic-level prediction of drug-induced liver injury. The method demonstrates that several physiological situations can be accurately modelled as can the effect of perturbations induced by drugs. It can also be used along with high-throughput 'omic' data to generate testable hypotheses leading to informed decision-making.
Subramanian
Kalyanasundaram
K
Strand Life Sciences Pvt Ltd, 237 C V Raman Avenue, RMV Extension, Sadashivnagar, 560080, Bangalore, India. kas@strandls.com
Raghavan
Sowmya
S
Rajan Bhat
Anupama
A
Das
Sonali
S
Bajpai Dikshit
Jyoti
J
Kumar
Rajeev
R
Narasimha
Mandyam Krishnakumar
MK
Nalini
Rajeswara
R
Radhakrishnan
Rajesh
R
Raghunathan
Srivatsan
S
D016907:Adverse Drug Reaction Reporting Systems; D000826:Animal Testing Alternatives; D000818:Animals; D056486:Chemical and Drug Induced Liver Injury / Q000209:etiology*; D004353:Drug Evaluation, Preclinical / Q000379:methods; D006706:Homeostasis / Q000187:drug effects; D006801:Humans; D008099:Liver / Q000187:drug effects* / Q000473:pathology; D008954:Models, Biological; D049490:Systems Biology / Q000379:methods*