SubQ-Sim: A Subcutaneous Physiologically Based Biopharmaceutics Model. Part 1: The Injection and System Parameters.

PURPOSE: To construct a detailed mechanistic and physiologically based biopharmaceutics model capable of predicting 1) device-formulation-tissue interaction during the injection process and 2) binding, degradation, local distribution, diffusion, and drug absorption, following subcutaneous injection. This paper is part of a series and focusses on the first aspect. METHODS: A mathematical model, SubQ-Sim, was developed incorporating the details of the various substructures within the subcutaneous environment together with the calculation of dynamic drug disposition towards the lymph ducts and venous capillaries. Literature was searched to derive key model parameters in healthy and diseased subjects. External factors such as body temperature, exercise, body position, food or stress provide a means to calculate the impact of "life events" on the pharmacokinetics of subcutaneously administered drugs. RESULTS: The model predicts the tissue backpressure time profile during the injection as a function of injection rate, volume injected, solution viscosity, and interstitial fluid viscosity. The shape of the depot and the concentrations of the formulation and proteins in the depot are described. The model enables prediction of formulation backflow following premature needle removal and the resulting formulation losses. Finally, the effect of disease (type 2 diabetes) or the presence of recombinant human hyaluronidase in the formulation on the injection pressure, are explored. CONCLUSIONS: This novel model can successfully predict tissue back pressure, depot dimensions, drug and protein concentration and formulation losses due to incorrect injection, which are all important starting conditions for predicting drug absorption from a subcutaneous dose. The next article will describe the absorption model and validation against clinical data.

IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 4: Prediction accuracy and software comparisons with improved data and modelling strategies.

Oral drug absorption is a complex process depending on many factors, including the physicochemical properties of the drug, formulation characteristics and their interplay with gastrointestinal physiology and biology. Physiological-based pharmacokinetic (PBPK) models integrate all available information on gastro-intestinal system with drug and formulation data to predict oral drug absorption. The latter together with in vitro-in vivo extrapolation and other preclinical data on drug disposition can be used to predict plasma concentration-time profiles in silico. Despite recent successes of PBPK in many areas of drug development, an improvement in their utility for evaluating oral absorption is much needed. Current status of predictive performance, within the confinement of commonly available in vitro data on drugs and formulations alongside systems information, were tested using 3 PBPK software packages (GI-Sim (ver.4.1), Simcyp® Simulator (ver.15.0.86.0), and GastroPlus™ (ver.9.0.00xx)). This was part of the Innovative Medicines Initiative (IMI) Oral Biopharmaceutics Tools (OrBiTo) project. Fifty eight active pharmaceutical ingredients (APIs) were qualified from the OrBiTo database to be part of the investigation based on a priori set criteria on availability of minimum necessary information to allow modelling exercise. The set entailed over 200 human clinical studies with over 700 study arms. These were simulated using input parameters which had been harmonised by a panel of experts across different software packages prior to conduct of any simulation. Overall prediction performance and software packages comparison were evaluated based on performance indicators (Fold error (FE), Average fold error (AFE) and absolute average fold error (AAFE)) of pharmacokinetic (PK) parameters. On average, PK parameters (Area Under the Concentration-time curve (AUC0-tlast), Maximal concentration (Cmax), half-life (t1/2)) were predicted with AFE values between 1.11 and 1.97. Variability in FEs of these PK parameters was relatively high with AAFE values ranging from 2.08 to 2.74. Around half of the simulations were within the 2-fold error for AUC0-tlast and around 90% of the simulations were within 10-fold error for AUC0-tlast. Oral bioavailability (Foral) predictions, which were limited to 19 APIs having intravenous (i.v.) human data, showed AFE and AAFE of values 1.37 and 1.75 respectively. Across different APIs, AFE of AUC0-tlast predictions were between 0.22 and 22.76 with 70% of the APIs showing an AFE > 1. When compared across different formulations and routes of administration, AUC0-tlast for oral controlled release and i.v. administration were better predicted than that for oral immediate release formulations. Average predictive performance did not clearly differ between software packages but some APIs showed a high level of variability in predictive performance across different software packages. This variability could be related to several factors such as compound specific properties, the quality and availability of information, and errors in scaling from in vitro and preclinical in vivo data to human in vivo behaviour which will be explored further. Results were compared with previous similar exercise when the input data selection was carried by the modeller rather than a panel of experts on each in vitro test. Overall, average predictive performance was increased as reflected in smaller AAFE value of 2.8 as compared to AAFE value of 3.8 in case of previous exercise.

Discovery of a Thiadiazole-Pyridazine-Based Allosteric Glutaminase 1 Inhibitor Series That Demonstrates Oral Bioavailability and Activity in Tumor Xenograft Models.

Tumors have evolved a variety of methods to reprogram conventional metabolic pathways to favor their own nutritional needs, including glutaminolysis, the first step of which is the hydrolysis of glutamine to glutamate by the amidohydrolase glutaminase 1 (GLS1). A GLS1 inhibitor could potentially target certain cancers by blocking the tumor cell's ability to produce glutamine-derived nutrients. Starting from the known GLS1 inhibitor bis-2-(5-phenylacetamido-1,2,4-thiadiazol-2-yl)ethyl sulfide, we describe the medicinal chemistry evolution of a series from lipophilic inhibitors with suboptimal physicochemical and pharmacokinetic properties to cell potent examples with reduced molecular weight and lipophilicity, leading to compounds with greatly improved oral exposure that demonstrate in vivo target engagement accompanied by activity in relevant disease models.

Discovery of AZD3514, a small-molecule androgen receptor downregulator for treatment of advanced prostate cancer.

Removal of the basic piperazine nitrogen atom, introduction of a solubilising end group and partial reduction of the triazolopyridazine moiety in the previously-described lead androgen receptor downregulator 6-[4-(4-cyanobenzyl)piperazin-1-yl]-3-(trifluoromethyl)[1,2,4]triazolo[4,3-b]pyridazine (1) addressed hERG and physical property issues, and led to clinical candidate 6-(4-{4-[2-(4-acetylpiperazin-1-yl)ethoxy]phenyl}piperidin-1-yl)-3-(trifluoromethyl)-7,8-dihydro[1,2,4]triazolo[4,3-b]pyridazine (12), designated AZD3514, that is being evaluated in a Phase I clinical trial in patients with castrate-resistant prostate cancer.

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.

Toward prediction of alkane/water partition coefficients.

Partition coefficients were measured for 47 compounds in the hexadecane/water ( P hxd) and 1-octanol/water ( P oct) systems. Some types of hydrogen bond acceptor presented by these compounds to the partitioning systems are not well represented in the literature of alkane/water partitioning. The difference, DeltalogP, between logP oct and logP hxd is a measure of the hydrogen bonding potential of a molecule and is identified as a target for predictive modeling. Minimized molecular electrostatic potential ( V min) was shown to be an effective predictor of the contribution of hydrogen bond acceptors to DeltalogP. Carbonyl oxygen atoms were found to be stronger hydrogen bond acceptors for their electrostatic potential than heteroaromatic nitrogen or oxygen bound to hypervalent sulfur or nitrogen. Values of V min calculated for hydrogen-bonded complexes were used to explore polarization effects. Predicted logP hxd and DeltalogP were shown to be more effective than logP oct for modeling brain penetration for a data set of 18 compounds.

Matched molecular pairs as a guide in the optimization of pharmaceutical properties; a study of aqueous solubility, plasma protein binding and oral exposure.

By identifying every pair of molecules that differ only by a particular, well-defined, structural transformation in a database of measured properties and computing the corresponding change in property, we obtain an overview of the effect that structural change has upon the property and set an expectation for what will happen when that transformation is applied elsewhere. The mean change indicates the expected magnitude of the change in the property and the number of cases in which the property increases give the probability that the structural transformation will cause the property to increase. Outliers indicate potential ways of avoiding the general trend. Comparing to changes in lipophilicity highlights structural transformations that have unusual effects, some of which can be explained by conformational changes. In this paper, we focus upon the effects on aqueous solubility, plasma protein binding and oral exposure of adding substituents to aromatic rings and methylating heteroatoms.

Different transition-state structures for the reactions of beta-lactams and analogous beta-sultams with serine beta-lactamases.

Beta-sultams are the sulfonyl analogues of beta-lactams, and N-acyl beta-sultams are novel inactivators of the class C beta-lactamase of Enterobacter cloacae P99. They sulfonylate the active site serine residue to form a sulfonate ester which subsequently undergoes C-O bond fission and formation of a dehydroalanine residue by elimination of the sulfonate anion as shown by electrospray ionization mass spectroscopy. The analogous N-acyl beta-lactams are substrates for beta-lactamase and undergo enzyme-catalyzed hydrolysis presumably by the normal acylation-deacylation process. The rates of acylation of the enzyme by the beta-lactams, measured by the second-order rate constant for hydrolysis, kcat/K(m), and those of sulfonylation by the beta-sultams, measured by the second-order rate constant for inactivation, k(i), both show a similar pH dependence to that exhibited by the beta-lactamase-catalyzed hydrolysis of beta-lactam antibiotics. Electron-withdrawing groups in the aryl residue of the leaving group of N-aroyl beta-lactams increase the rate of alkaline hydrolysis and give a Bronsted beta(lg) of -0.55, indicative of a late transition state for rate-limiting formation of the tetrahedral intermediate. Interestingly, the corresponding Bronsted beta(lg) for the beta-lactamase-catalyzed hydrolysis of the same substrates is -0.06, indicative of an earlier transition state for the enzyme-catalyzed reaction. By contrast, although the Bronsted beta(lg) for the alkaline hydrolysis of N-aroyl beta-sultams is -0.73, similar to that for the beta-lactams, that for the sulfonylation of beta-lactamase by these compounds is -1.46, compatible with significant amide anion expulsion/S-N fission in the transition state. In this case, the enzyme reaction displays a later transition state compared with hydroxide-ion-catalyzed hydrolysis of the beta-sultam.

Novel mechanism of inhibiting beta-lactamases by sulfonylation using beta-sultams.

Beta-sultams are the sulfonyl analogues of beta-lactams and N-acyl beta-sultams are novel inactivators of the class C beta-lactamase of Enterobacter cloacae P99. The rates of inactivation show a similar pH-rate dependence as that exhibited by the beta-lactam antibiotics and with ESIMS data it is suggested that beta-sultams sulfonylate the active site serine residue to form a sulfonate ester.

Structure-reactivity relationships in the inactivation of elastase by beta-sultams.

N-Acyl-beta-sultams are time dependent irreversible active site directed inhibitors of elastase. The rate of inactivation is first order with respect to beta-sultam concentration and the second order rate constants show a similar dependence on pH to that for the hydrolysis of a peptide substrate. Inactivation is due to the formation of a stable 1:1 enzyme inhibitor complex as a result of the active site serine being sulfonylated by the beta-sultam. Ring opening of the beta-sultam occurs by S-N fission in contrast to the C-N fission observed in the acylation of elastase by N-acylsulfonamides. Structure-activity effects are compared between sulfonylation of the enzyme and alkaline hydrolysis. Variation in 4-alkyl and N-substituted beta-sultams causes differences in the rates of inactivation by 4 orders of magnitude.

Hydrolysis of a sulfonamide by a novel elimination mechanism generated by carbanion formation in the leaving group.

The alkaline hydrolysis of N-alpha-methoxycarbonyl benzyl-beta-sultam occurs 10(3) times faster than the corresponding carboxylate and with rapid D-exchange at the alpha-carbon: the pH rate profile indicates pre-equilibirum CH ionisation and together with formation of benzoyl formate as a product this suggests a novel mechanism for hydrolysis.