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.

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.

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.

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.

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.

Inflammation is accompanied by increased endothelial chemokine production and adhesion molecule expression, which may result in an extensive neutrophil infiltration. As such, the search for novel anti-inflammatory substances able to downregulate these parameters, as well as tissue damage, holds therapeutic promise.

Analytical identification of metabolites for a drug candidate is usually a time consuming and low-throughput task and is performed only at the later phases of drug development. Therefore the possibility to predict possible sites of human liver microsomal (HLM) metabolism using in silico techniques would be a very attractive feature for any medicinal chemist.

Of all the challenges facing medicinal chemists in general, one of the most significant must be transforming an active molecule into a viable drug. Lead optimization efforts are guided by a combination of factors, such as potency, ease of synthesis, patentability concerns, specific synthetic constrains of the interaction with the target, as well as the lead’s toxicity and ADME properties.

We present the results of initial work carried out within the OpenToxLink Virtual Organization, applying a Weight-of-Evidence (WoE) approach based on consensus across multiple sources of information for the prediction of adverse effects of a large set of potential antimalarial compounds. The work was carried out as part of the EU FP7 project SYNERGY, evaluating the support of decision dashboards and event-driven collaborative research of software developed within SYNERGY.

The estrogen receptors (ER) refer to a group of the nuclear hormone receptor superfamily of ligand-mediated transcriptional factors. Over expression of this type of receptors leads to a breast cancer progression. Hormone-responsive breast cancer develops resistance to conventional anti-cancer therapy, and this becomes a major problem in a breast cancer therapy.