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A physiologically based pharmacokinetic model was developed to describe the tissue distribution kinetics of a dendritic nanoparticle and its conjugated active pharmaceutical ingredient (API) in plasma, liver, spleen, and tumors. Tumor growth data from MV-4-11 tumor-bearing mice were incorporated to investigate the exposure/efficacy relationship. The nanoparticle demonstrated improved antitumor activity compared to the conventional API formulation, owing to the extended released API concentrations at the site of action. Model simulations further enabled the identification of critical parameters that influence API exposure in tumors and downstream efficacy outcomes upon nanoparticle administration. The model was utilized to explore a range of dosing schedules and their effect on tumor growth kinetics, demonstrating the improved antitumor activity of nanoparticles with less frequent dosing compared to the same dose of naked APIs in conventional formulations.

Proteolysis-targeting chimeras (PROTACs) are an emerging therapeutic modality with the potential to open target space not accessible to conventional small molecules via a degradation-based mechanism; however, their bifunctional nature can result in physicochemical properties that breach commonly accepted limits for small-molecule oral drugs. We offer a drug metabolism and pharmacokinetics (DMPK) perspective on the optimisation of oral PROTACs across a diverse set of projects within Oncology R&D at AstraZeneca, highlighting some of the challenges that they have presented to our established screening cascade. Furthermore, we challenge some of the perceptions and dogma surrounding the feasibility of oral PROTACS and demonstrate that acceptable oral PK properties for this modality can be regularly achievable despite the physicochemical property challenges they present.

Herein we report the optimization of a series of tricyclic indazoles as selective estrogen receptor degraders (SERD) and antagonists for the treatment of ER+ breast cancer. Structure based design together with systematic investigation of each region of the molecular architecture led to the identification of N-[1-(3-fluoropropyl)azetidin-3-yl]-6-[(6S,8R)-8-methyl-7-(2,2,2-trifluoroethyl)-6,7,8,9-tetrahydro-3H-pyrazolo[4,3-f]isoquinolin-6-yl]pyridin-3-amine (28). This compound was demonstrated to be a highly potent SERD that showed a pharmacological profile comparable to fulvestrant in its ability to degrade ERα in both MCF-7 and CAMA-1 cell lines. A stringent control of lipophilicity ensured that 28 had favorable physicochemical and preclinical pharmacokinetic properties for oral administration. This, combined with demonstration of potent in vivo activity in mouse xenograft models, resulted in progression of this compound, also known as AZD9833, into clinical trials.

During drug discovery and prior to the first human dose of a novel candidate drug, the pharmacokinetic (PK) behavior of the drug in humans is predicted from preclinical data. This helps to inform the likelihood of achieving therapeutic exposures in early clinical development. Once clinical data are available, the observed human PK are compared with predictions, providing an opportunity to assess and refine prediction methods. Application of best practice in experimental data generation and predictive methodologies, and a focus on robust mechanistic understanding of the candidate drug disposition properties before nomination to clinical development, have led to maximizing the probability of successful PK predictions so that 83% of AstraZeneca drug development projects progress in the clinic with no PK issues; and 71% of key PK parameter predictions [64% of area under the curve (AUC) predictions; 78% of maximum concentration (Cmax) predictions; and 70% of half-life predictions] are accurate to within twofold. Here, we discuss methods to predict human PK used by AstraZeneca, how these predictions are assessed and what can be learned from evaluating the predictions for 116 candidate drugs.

Background: DMPK data and knowledge are critical in maximising the probability of developing successful drugs via the application of in silico, in vitro and in vivo approaches in drug discovery. Methods: The evaluation, optimisation and prediction of human pharmacokinetics is now a mainstay within drug discovery. These elements are at the heart of the ‘right tissue’ component of AstraZeneca’s ‘5Rs framework’ which, since its adoption, has resulted in increased success of Phase III clinical trials. With the plethora of DMPK related assays and models available, there is a need to continually refine and improve the effectiveness and efficiency of approaches best to facilitate the progression of quality compounds for human clinical testing. Results: This article builds on previously published strategies from our laboratories, highlighting recent discoveries and successes, that brings our AstraZeneca Oncology DMPK strategy up to date. We review the core aspects of DMPK in Oncology drug discovery and highlight data recently generated in our laboratories that have influenced our screening cascade and experimental design. We present data and our experiences of employing cassette animal PK, as well as re-evaluating in vitro assay design for metabolic stability assessments and expanding our use of freshly excised animal and human tissue to best inform first time in human dosing and dose escalation studies. Conclusion: Application of our updated drug-drug interaction and central nervous system drug exposure strategies are exemplified, as is the impact of physiologically based pharmacokinetic and pharmacokinetic-pharmacodynamic modelling for human predictions.

Due to the blood-brain barrier (BBB) limiting the exposure of therapeutics to the central nervous system (CNS), patients with brain malignancies are challenging to treat, typically have poor prognoses, and represent a significant unmet medical need. Preclinical data report osimertinib to have significant BBB penetration and emerging clinical data demonstrate encouraging activity against CNS malignancies. Here, we discuss the oncology drug candidates AZD3759 and AZD1390 as case examples of discovery projects designing in BBB penetrance. We demonstrate how these innovative kinase inhibitors were recognized as brain penetrant and outline our view of experimental approaches and strategies that can facilitate the discovery of new brain-penetrant therapies for the treatment of primary and secondary CNS malignancies as well as other CNS disorders.

N-(5-Bromo-3-methoxypyrazin-2-yl)-5-chlorothiophene-2-sulfonamide 1 was identified as a hit in a CCR4 receptor antagonist high-throughput screen (HTS) of a subset of the AstraZeneca compound bank. As a hit with a lead-like profile, it was an excellent starting point for a CCR4 receptor antagonist program and enabled the rapid progression through the Lead Identification and Lead Optimization phases resulting in the discovery of two bioavailable CCR4 receptor antagonist candidate drugs.

This review promotes the value of isolated hepatocytes in modern Drug Discovery programmes and outlines how increased understanding, particularly in the area of in vitro-in vivo extrapolation (IVIVE), has led to more widespread use. The importance of in vitro metabolic intrinsic clearance data for predicting in vivo clearance has been acknowledged for several years and the greater utility of hepatocytes, compared with hepatic microsomes and liver slices, for this application is discussed. The application of hepatocytes in predicting drug-drug interactions (DDIs) resulting from reversible and irreversible (time-dependent) inhibition is relatively novel but affords the potential to study both phase I and phase II processes together with any impact of drug efflux and/or uptake (cellular accumulation). Progress in this area is reviewed along with current opinions on the comparative use of primary hepatocytes and higher throughput reporter gene-based systems for studying cytochrome P450 (CYP) induction. The appreciation of the role of transporter proteins in drug disposition continues to evolve. The study of hepatic uptake using isolated hepatocytes and the interplay between drug transport and metabolism with respect to both clearance and DDIs and subsequent IVIVE is also considered.

Based on a robust understanding of how physicochemical properties drive PK, relatively little experimental data is required establish a drug discovery optimisation strategy and gain confidence that clinical candidates are selected with a high likelihood of achieving an acceptable clinical PK profile. This chapter is designed to be used by the practicing medicinal chemist and attempts to provide both the context and some specific advice to apply best practice for PK and efficacious dose prediction. Hints and tips are suggested throughout the chapter and methods to predict human PK parameters outlined. Worked examples of both proprietary candidate and approved drugs are used to highlight particular themes. This chapter can be used in conjunction with the associated Dose to Man iPad app which allows medicinal chemists to simulate therapeutic doses and exposures in Man for their drug discovery projects via the approaches and equations presented herein. ‘Dose to man’ approach integrates information to rank and select compounds, which as a minimum, is a sophisticated scoring function, and at best, is an effective tool for assessing clinical utility.

In the present age of pharmaceutical research and development, focused delivery of decision making data is more imperative than ever before. Resulting from several years' success, failure and consequential learning, this article also proffers advice and guidance on which in vitro and in vivo experiments to perform to facilitate efficient and cost-effective pursuit of candidate drugs with acceptable human pharmacokinetic profiles. Predictive in silico models are important in directing design toward compounds with the highest probability of having suitable DMPK properties rather than in predicting human pharmacokinetics per se, and the value and utility of such approaches are reviewed with the intention of providing direction to DMPK scientists. Relating to absorption, distribution, elimination and effective half-life, strategies are described to provide direction in commonly encountered scenarios.

The CYP family of enzymes are the primary facilitators of oxidative biotransformation in the liver and are responsible for the metabolism of the majority of human drugs. The CYP family metabolize a very broad range of substrates and play a central role in the mediation of clinically relevant drug–drug interactions (DDIs). This article summarizes the current knowledge base and the complexities of CYP inhibition and provides a guide for embarking on prediction of clinical DDIs with particular emphasis on the drug discovery setting. Keywords: drug–drug interactions (DDIs); inhibition; cytochrome P450; substrate selection; inhibitors

Starting from adenosine triphosphate (ATP), the identification of a novel series of P2Y(12) receptor antagonists and exploitation of their SAR is described. Modifications of the acidic side chain and the purine core and investigation of hydrophobic substituents led to a series of neutral molecules. The leading compound, 17 (AZD6140), is currently in a large phase III clinical trial for the treatment of acute coronary syndromes and prevention of thromboembolic clinical sequelae.