|Why Is My Assay Failing? An Approach to Assay Equipment Optimization|
Tanya R. Knaide, John Thomas Bradshaw, Kevin Khovananth, Keith Albert
Assays can produce unexpected or failing results for a multitude of reasons. Variability may be introduced at any point within the assay process.
|Validation of an Automated Cell-Based Bioluminescent TNFa Blocker Bioassay|
Brad Larson, Tracy Worzella, Rich Moravec, Neal Cosby, Frank Fan, Teresa Surowy and Peter Banks
TNFa blocker biopharmaceuticals represent an important and successful class of protein drugs used in the treatment of several autoimmune diseases. Bioassays are indispensible tools in biopharmaceutical drug development and commercialization that are used to quantify biological activity and stability of drugs or drug candidates. The automation of these assays can serve to create an accurate, robust process which can allow the researcher to perform other more important functions.
|Modeling Disposition of Sotalol following Intravenous and Oral Administration in Healthy Adult Subjects|
S. Ray Chaudhuri, V. Lukacova and W. S. Woltosz
Sotalol is a non specific adrenergic beta-antagonist that is used in the treatment of life-threatening arrhythmia. Its absorption, distribution and systemic PK or, collectively, ‘disposition’ was modeled and simulated using GastroPlus™ v7.0. Biopharmaceutical properties were obtained from in silico predictions and in vitro measurements.
|Predicting hERG Potassium Channel Affinity with Artificial Neural Network Ensembles|
Adam C. Lee, GrazynaFraczkiewicz, Robert Fraczkiewicz, Robert D. Clark and Walter S. Woltosz
Modeling hERG inhibition has gained significant popularity since 2005, when the FDA recognized the correlation between hERG inhibition and a prolonged QT interval by issuing guidance for the evaluation of new non-antiarrythmic drugs against the hERG channel.Long QT syndrome or LQTS is a risk factor for ventricular tachyarrhythmias and sudden death.
|Predicting Sites of Metabolism with Artificial Neural Network Ensembles|
Marvin Waldman, Robert Fraczkiewicz, JinhuaZhang, Robert D. Clark and Walter S. Woltosz
Hepatic first-pass metabolism of many drugs and pro drugs plays a key role in their oral bioavailability. The human cytochrome P450 enzymes are responsible for the metabolism of most drugs. Knowledge of likely sites of metabolic attack in a drug molecule can aid in designing out unwanted metabolic liabilities early on in the drug discovery process, as well as in the design of pro drugs where metabolic transformation is desired.
|Be Careful What You Ask for: Challenges of Predicting Human Clearance for a Low Metabolic Turnover Compound, ELND006|
Kevin Quinn, David Nakamura, Heather Zhang, Shawn Gauby, Colin Lorentzen, Erich Goldbach, Amanda Moore, Salman Khetani, Earvin Liang, John-Michael Sauer and George Tonn,
A study of in vitro clearance of ELND006, a low turn-over compound.
|Global Gene Expression Changes Induced In Primary Human Hepatocytes By Thiazolidinediones Upon Repeat Dosing of HepatoPac™ Cultures|
Michael McVay and Salman R. Khetani
An assessment of global gene expression changes in HepatoPac, a micropatterned co-culture of hepatocytes and stromal cells.
|A Long Term Culture Model for Primary Hepatocytes from Cynomolgus Monkeys|
Simon Aoyama, Sara Lambirth, Chitra Kanchagar and Salman R. Khetani
The Macaca fascicularis or cynomolgus monkey is a non-human primate often used in pre-clinical animal studies. In this study, we applied microtechnology and tissue engineering techniques to cynomologus monkey hepatocytes in order to determine if these cells could be stabilized in micropatterned co-cultures similar to their human and rat counterparts.
|Live Cell Beating Assay Using Human iPSC-derived Cardiomyocytes for Evaluation of Drug Efficacy and Toxicity|
Oksana Sirenko, Carole Crittenden, Blake Anson, Jayne Hesley, Yen-Wen Chen, Nick Callamaras and Evan F. Cromwell
A large percentage of new drugs fail in clinical studies due to cardiac toxicity. Development of highly predictive in vitro assays suitable for screening, safety assessment or other environments is therefore extremely important for drug development. Human cardiomyocytes derived from stem cell sources can greatly accelerate the discovery of cardiac drugs and improve drug safety by offering more clinically relevant cell-based models than those presently available.