Preventing Late Stage Failures with Reliable In Silico ADME and Tox Prediction

In silico prediction of ADME and Tox properties allow you to investigate all the avenues that can help improve your processes and make you proactive. Drug recalls are generally related to ADME and Tox properties of drugs that lead to serious health effects not identified in discovery, development, or clinical trials. While it may not be possible to completely eradicate this type of late failure, the pharmaceutical industry certainly aspires to it.

Visit ACD/Labs at Booth 1123 in the exhibition hall to learn more and see demonstrations of ACD/ADME Suite and ACD/Tox Suite.

One of the most exciting things about working in pharmaceutical R&D is the ever-changing environment. The emergence of new technologies, improved instruments, and new techniques fuels the scientific minds that dedicate their careers to the advancement of science. The changes come as a result of innovations made in the course of research—a more accurate and effective assay for measurement of biochemical function; a modified reagent to effect a functional group transformation—and to improve processes so that negative outcomes can be avoided.

In silico prediction of ADMET properties is just one of the tools available to R&D scientists. While manual/high-throughput experiments are the traditional choice, computational prediction provides numerous benefits:

• No physical sample is required—ADME and toxicity studies can begin at the outset of discovery with virtual screening.
• Precious samples can be saved for key experiments—use software to predict for certain endpoints, and help guide your other experiments so that your resources can be well allocated.

From the many software providers that offer ADME/Tox predictors, the newest is ACD/Labs. As a result of their merger with Pharma Algorithms in February of this year, they added ADME and Tox expertise to their repertoire of property predictors. What sets them apart from other vendors? A clean simple interface, models based on a strong scientific foundation, and a customer-centric product. Unlike other predictors, with ACD/ADME Suite and ACD/Tox Suite you are not left wondering about the reliability of the prediction. The Reliability Index clearly shows whether your chemical space is appropriately represented in the training sets. Moreover, if the reliability is low, add your experimental data (from whatever protocols you use in-house) to expand chemical space coverage to your area of interest, and improve prediction accuracy.