Robert D. M. Davies

Making medicinal chemistry more effective—application of Lean Sigma to improve processes, speed and quality

The pharmaceutical industry, particularly the small molecule domain, faces unprecedented challenges of escalating costs, high attrition as well as increasing competitive pressure from other companies and from new treatment modes such as biological products. In other industries, process improvement approaches, such as Lean Sigma, have delivered benefits in speed, quality and cost of delivery. Examining the medicinal chemistry contributions to the iterative improvement process of design-make-test-analyse from a Lean Sigma perspective revealed that major improvements could be made. Thus, the cycle times of synthesis, as well as compound analysis and purification, were reduced dramatically. Improvements focused on team, rather than individual, performance. These new ways of working have consequences for staff engagement, goals, rewards and motivation, which are also discussed.

Cubanes in Medicinal Chemistry: Synthesis of Functionalized Building Blocks

A collection of novel, pharmaceutically relevant cubane-containing molecules has been prepared from the commercially available cubane-1,4-dimethylester. A range of synthetic methods have been applied to prepare these cubane building blocks with one or two functional handles to allow easy incorporation into existing medicinal chemistry programs.

Identification, optimisation and in vivo evaluation of oxadiazole DGAT-1 inhibitors for the treatment of obesity and diabetes

A novel series of DGAT-1 inhibitors was discovered from an oxadiazole amide high throughput screening (HTS) hit. Optimisation of potency and ligand lipophilicity efficiency (LLE) resulted in a carboxylic acid containing clinical candidate 53 (AZD3988), which demonstrated excellent DGAT-1 potency (0.6 nM), good pharmacokinetics and pre-clinical in vivo efficacy that could be rationalised through a PK/PD relationship.

Design and optimization of pyrazinecarboxamide-based inhibitors of diacylglycerol acyltransferase 1 (DGAT1) leading to a clinical candidate dimethylpyrazinecarboxamide phenylcyclohexylacetic acid (AZD7687).

A new series of pyrazinecarboxamide DGAT1 inhibitors was designed to address the need for a candidate drug with good potency, selectivity, and physical and DMPK properties combined with a low predicted dose in man. Rational design and optimization of this series led to the discovery of compound 30 (AZD7687), which met the project objectives for potency, selectivity, in particular over ACAT1, solubility, and preclinical PK profiles. This compound showed the anticipated excellent pharmacokinetic properties in human volunteers.

Identification of pyrazolo-pyrimidinones as GHS-R1a antagonists and inverse agonists for the treatment of obesity

A pyrazolo-pyrimidinone based series of growth hormone secretagogue receptor type 1a (GHS-R1a) antagonists and inverse agonists were identified using a scaffold hop from known quinazolinone GHS-R1a modulators. Lipophilicity was reduced to decrease hERG activity while maintaining GHS-R1a affinity. SAR exploration of a piperidine substituent was used to identify small cyclic groups as a functional switch from partial agonists to neutral antagonists and inverse agonists. A tool compound was identified which had good overall properties and sufficient oral plasma and CNS exposure to demonstrate reduced food intake in mice through a mechanism involving GHS-R1a.

Identification, optimization, and pharmacology of acylurea GHS-R1a inverse agonists.

Ghrelin plays a major physiological role in the control of food intake, and inverse agonists of the ghrelin receptor (GHS-R1a) are widely considered to offer utility as antiobesity agents by lowering the set-point for hunger between meals. We identified an acylurea series of ghrelin modulators from high throughput screening and optimized binding affinity through structure-activity relationship studies. Furthermore, we identified specific substructural changes, which switched partial agonist activity to inverse agonist activity, and optimized physicochemical and DMPK properties to afford the non-CNS penetrant inverse agonist 22 (AZ-GHS-22) and the CNS penetrant inverse agonist 38 (AZ-GHS-38). Free feeding efficacy experiments showed that CNS exposure was necessary to obtain reduced food intake in mice, and it was demonstrated using GHS-R1a null and wild-type mice that this effect operates through a mechanism involving GHS-R1a.

Matched triplicate design sets in the optimisation of glucokinase activators – maximising medicinal chemistry information content

Successful lead optimisation requires the identification of the best compound within the chemical space explored during an optimisation campaign. This can be a costly and inefficient process leading to the synthesis of many sub-optimal compounds. In this paper, a method for carrying out this exercise more effectively is outlined. This relies on the generation of robust datasets on which to build predictive models in a paradigm termed “matched triplicate design sets”. The practical implementation of this approach is exemplified in the optimisation of a new series of glucokinase activators.

Tetrahydroisoquinoline Phenols: Selective Estrogen Receptor Downregulator Antagonists with Oral Bioavailability in Rat

A series of tetrahydroisoquinoline phenols was modified to give an estrogen receptor downregulator-antagonist profile. Optimization around the core, alkyl side chain, and pendant aryl ring resulted in compounds with subnanomolar levels of potency. The phenol functionality was shown to be required to achieve highly potent compounds, but unusually this was compatible with obtaining high oral bioavailabilities in rat.

Optimising pharmacokinetics of glucokinase activators with matched triplicate design sets – the discovery of AZD3651 and AZD9485

The matched triplicate approach to lead optimisation offers a means of generating more robust quantitative structure activity relationship data and this rigour leads to better quality decision making and greater ability to predict optimal compounds within a series. One of the ultimate aims of this approach is to use the data generated to build more accurate predictive models to identify the best compounds within the exemplified chemical space in an efficient manner. This paper describes the continued application of this approach to the optimisation of a series of glucokinase activators. This second phase focussed primarily on the rational solution to plasma instability observed with the previous compounds and, hence, achieved acceptable oral exposure in the series. The campaign was completed by using the predictive power of Free-Wilson analysis based on the matched triplicate datasets to enable a focussed, matrix based endgame culminating in the identification of two development candidates, AZD3651 and AZD9485.

Design and synthesis of a novel series of cyclohexyloxy-pyridyl derivatives as inhibitors of diacylglycerol acyl transferase 1

A novel series of potent diacylglycerol acyl transferase 1 inhibitors was developed from the clinical candidate AZD3988. Replacement of the phenyl cyclohexyl-ethanoate side chain with substituted oxy-linked side chains to introduce changes in shape and polarity, reduce lipophilicity and mask the hydrogen bond donors with internal hydrogen bond acceptors led to improvements in solubility, unbound clearance and excellent selectivity over the related enzyme acyl-coenzyme A:cholesterol acyltransferase 1. A comparison of the small molecule crystal structures of compound 4 and compound 28 is described. Compounds in this series have good ADMET properties and provide an exposure-dependent decrease in circulating plasma triglyceride levels in a rat oral lipid tolerance test.