QST and the Transformation in Drug Safety Assessment
Paul B. Watkins, M.D. FAASLD
Director, Institute for Drug Safety Sciences , University of North Carolina=
in Chapel Hill
Wednesday December 16, 2020, 12:00 to 1:00 pm EDT
Register for free at
https://www.rosaandco.com/webinars
Abstract:
Establishing the safety of new drug candidates is a major hurdle to drug de=
velopment as standard preclinical toxicology does not reliably predict huma=
n adverse drug events. Liver toxicity is a potentially fatal adverse event =
that has been particularly challenging to predict from preclinical studies.=
Moreover, abnormalities in serum liver chemistries are commonly observed i=
n clinical trials raising suspicion of liver safety liability that can curr=
ently only be removed with very large clinical trials. This talk will focus=
on the progress of a public-private partnership (the DILI-sim Initiative) =
that for the last decade has been developing a Quantitative Systems Toxicol=
ogy (QST) model (DILIsym(r)) to improve mechanistic understanding and there=
fore prediction of liver safety liabilities of new drug candidates.
The DILIsym model uses PBPK and other available data to determine the conce=
ntration of parent drug and major metabolites inside the hepatocyte during =
various dosing regimens. Also fed into the model are the exposure dependent=
effects of parent drug and major metabolites on oxidative stress, bile aci=
d homeostasis, and mitochondrial function as measured in in vitro or cellul=
ar systems. Parameters in the model have been varied to reflect genetic and=
non-genetic variability to create a virtual healthy human population as we=
ll as disease-specific populations. With the data inputs, DILIsym will pred=
ict the incidence and severity of liver injury that will be observed in a s=
imulated patient population as a function of dosing regimen. Results of DIL=
Isym modeling are increasingly used in decision making within Pharma and ha=
ve also been helpful in interactions with regulators.
DILIsym provides an example of how increased application of QST modeling sh=
ould transform the safety assessment of new drug candidates as well as risk=
management in clinical trials and post-approval.
Received on Thu Dec 03 2020 - 10:00:38 EST
