Model To Predict Likelihood of Drug Birth Defect In Pregnancy

Researchers have created a preclinical model for predicting a drug's tendency to cause fetal malformations during pregnancy based on characterizing the genes that it targets.

The Children's Hospital Boston Informatics Program (CHIP) used bioinformatics and public databases to profile 619 drugs already assigned to a pregnancy risk class, and whose target genes or proteins are known.

The researchers found that drugs targeting a large proportion of genes associated with fetal development tended to be in the higher risk classes.

Based on the developmental gene profile, they created a model that showed 79 percent accuracy in predicting whether a drug would be in Class A (safest) or Class X (known teratogen).

When Schachter and Kohane applied the model to drugs across all risk classes, the proportion of developmental genes targeted roughly matched the degree of known risk.

"A lot of drugs in the middle of the spectrum, and maybe even some in Class A, may cause subtle defects that we haven't detected. We can't provide a yes/no answer, but we found a pattern that can predict which are riskier," said CHIP investigator Asher Schachter.

Given the degree of uncertainty, researchers believe their model may be of interest to drug developers and prescribing physicians, and might provide useful information to incorporate in drug labeling.

The findings were described in the journal Reproductive Toxicology.

Source: ANI