We present a novel computational approach for predicting human pharmacokinetics (PK) that addresses the challenges of early stage drug design. Our study introduces and describes a large-scale data set of 11 clinical PK end points, encompassing over 2700 unique chemical structures to train machine learning models. To that end multiple advanced training strategies are compared, including the integration of in vitro data and a novel self-supervised pretraining task.
View Article and Find Full Text PDFAlthough computational predictions of pharmacokinetics (PK) are desirable at the drug design stage, existing approaches are often limited by prediction accuracy and human interpretability. Using a discovery data set of mouse and rat PK studies at Roche (9,685 unique compounds), we performed a proof-of-concept study to predict key PK properties from chemical structure alone, including plasma clearance (CLp), volume of distribution at steady-state (Vss), and oral bioavailability (F). Ten machine learning (ML) models were evaluated, including Single-Task, Multitask, and transfer learning approaches (i.
View Article and Find Full Text PDF2-Aminooxazolines were discovered as a novel structural class of TAAR1 ligands. Starting from a known adrenergic compound 1, structural modifications were made to obtain highly potent and selective TAAR1 ligands such as 12 (RO5166017), 18 (RO5256390), 36 (RO5203648), and 48 (RO5263397). These compounds exhibit drug-like physicochemical properties, have good oral bioavailability, and display in vivo activity in a variety of animal models relevant for psychiatric diseases and addiction.
View Article and Find Full Text PDFBackground: Trace amines, compounds structurally related to classical biogenic amines, represent endogenous ligands of the trace amine-associated receptor 1 (TAAR1). Because trace amines also influence the activity of other targets, selective ligands are needed for the elucidation of TAAR1 function. Here we report on the identification and characterization of the first selective and potent TAAR1 partial agonist.
View Article and Find Full Text PDFA series of (3R,4R)-pyrrolidine-3,4-dicarboxylic acid amides was investigated with respect to their factor Xa inhibitory activity, selectivity, pharmacokinetic properties, and ex vivo antithrombotic activity. The clinical candidate from this series, R1663, exhibits excellent selectivity against a panel of serine proteases and good pharmacokinetic properties in rats and monkeys. A Phase I clinical study with R1663 has been finalized.
View Article and Find Full Text PDFStarting from a hit identified by focused screening, 3-aminopyrrolidine factor Xa inhibitors were designed. The binding mode as determined by X-ray structural analysis as well as the pharmacokinetic behaviour of selected compounds is discussed.
View Article and Find Full Text PDFThe discovery of a highly potent and selective tissue factor/factor VIIa inhibitor is described. Upon oral administration of its double prodrug in the guinea pig, a dose-dependent antithrombotic effect is observed in an established model of arterial thrombosis without prolonging bleeding time. The pharmacodynamic properties of this selective inhibitor are compared to the behaviour of a mixed factor VIIa/factor Xa inhibitor.
View Article and Find Full Text PDFWe describe the structure-based design and synthesis of highly potent, orally bioavailable tissue factor/factor VIIa inhibitors which interfere with the coagulation cascade by selective inhibition of the extrinsic pathway.
View Article and Find Full Text PDFBioorg Med Chem Lett
February 2005
Proof of concept experiments have shown that tissue factor/factor VIIa inhibitors have antithrombotic activity without enhancing bleeding propensity. Starting from lead compounds generated by a biased combinatorial approach, phenylglycine amide tissue factor/factor VIIa inhibitors with low nanomolar affinity and good selectivity against other serine proteases of the coagulation cascade were designed, using the guidance of X-ray structural analysis and molecular modelling.
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