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Enabling chiral separations in discovery chemistry with open-access chiral supercritical fluid chromatography
No full textWork from this paper details a novel walk-up open-access (OA) approach to enable chiral analytical method development and preparative separation of enantiomers in early discovery chemistry using supercritical fluid chromatography (SFC). We have demonstrated the success of this OA approach using immobilized chiral stationary phases (CSPs). After screening a diverse set of racemic drug candidates, we have concluded that a simplified OA chiral SFC platform can successfully purify approximately 60% of the analysed racemates. This streamlined OA workflow enables medicinal chemists with limited expertise in chiral method development to successfully and rapidly purify enantiomers for their projects using Waters UPC2 and Prep100-SFC instrumentation
Translatability of the S7A core battery respiratory safety pharmacology studies: Preclinical respiratory and related clinical adverse events
No full textIntroduction: Before entering into first-in-human studies, most new chemical entities must undergo a series of preclinical evaluations. ICH S7A safety pharmacology (SP) guidelines, adopted in 2001, include respiratory assessments as part of the core battery. Despite these safety measures being in place for nearly two decades, studies examining the relationship between preclinical findings captured in respiratory SP studies and clinical respiratory adverse events (AEs) are sparse. Therefore, the aim of this study is to evaluate the predictive value of preclinical respiratory observations to identify clinical respiratory AEs for both investigational products in early drug development and approved drugs. Method: Three independent databases were interrogated to evaluate the concordance between preclinical and clinical respiratory AEs. Two databases stem from early clinical phase studies, evaluating 52 and 128 investigational products respectively. The third database was derived from a large repository of nearly 4000 FDA and EMA drug approval documents. Results: Analysis of early phase clinical studies revealed little to no predictive risk for clinical respiratory adverse events when respiratory findings were observed in preclinical studies, with a positive predictive value (PPV) of 27% and 36% for each dataset respectively. In addition, the likelihood ratio, which reflects the shift in predictability of human risk, was 1.02 and 0.76 respectively, indicating no change in liability. Evaluation of approved drugs revealed a small shift in predictability for preclinical respiratory findings to translate into respiratory clinical AE, with likelihood ratios ranging from 2.5–3.4 and PPV of 18–29% for severe AEs such as lung disorder, respiratory depression and respiratory failure. Discussion: Altogether the translatability of preclinical respiratory findings into clinical AEs is low. Mandating dedicated respiratory SP studies as part of the core battery should be reconsidered in light of the low translatability of respiratory risk clinically and can be effectively incorporated into toxicology investigations
A New Semi-Automated Computer-Based System for Assessing the Purge of Mutagenic Impurities
No full textThe ICH M7 guidance provides a series of flexible control options for the control of potentially mutagenic impurities (PMIs) that fully align with key risk-based principles. This includes Option 4, which leverages existing process knowledge and/or data to justify control of PMIs without the need for routine analytical release testing during manufacturing. One such tech-nique highlighted uses systematic, semi-quantitative calculations to define the degree of “purge” of PMIs within a synthetic route to an API based on physicochemical properties of the impurities in question, and the manufacturing process being undertaken. This paper introduces a consortium-led initiative which aims to build on the semi-quantitative purge approach, and harmonise industry best practices by enabling the calculations to be conducted in a standardised, consistent and repro-ducible manner. The development of an expert-derived knowledge base for the prediction of reactivity by enhancing expert opinion using evidence derived from published literature and experimental data is also discussed. Furthermore, this paper describes the application of the Mirabilis software for the processes involved in the synthesis of Verbecestat, Naloxegol oxa-late and Camicinal
Identification and Application of Threonine Aldolase for Synthesis of valuable α-amino, β-hydroxy-Building Blocks
No full textChiral β-hydroxy α-amino acid structural motifs are interesting and common synthons present in multiple APIs and drug candidates. To access those chiral building blocks either multistep chemical synthesis is required or advantage can be taken from using threonine aldolases which catalyse aldol reaction between an aldehyde and glycine in a stereoselective way. Bioinformatics tools have been utilized to identify the gene of threonine aldolase from C. humicola and prepare its recombinant version from E. coli fermentation. This enzyme was planned to be implemented as a key step in the synthesis of API. Beside this application, aldolase was purified, characterized and further substrate scope of this enzyme was also investigated. Handful of enzymatic reactions was scale up and products were recovered to access the diastereoselectivity and scaleability of this assymetric synthetic approach towards β-hydroxy α-amino acid chiral building blocks
Traditional and digital biomarkers - two worlds apart?
No full textThe identification and application of biomarkers in the clinical and medical fields has an enormous impact on society. The increase of digital devices and the rise in popularity of health-related mobile apps has produced a new trove of biomarkers in large, diverse, and complex data. However, the unclear definition of digital biomarkers, population groups, and their intersection with traditional biomarkers, hinders their discovery and validation. We identify current issues in the field of digital biomarkers and put forth suggestions to address them during the DayOne Workshop with participants from academia, industry and regulatory agencies. We find similarities and differences between traditional and digital biomarkers in order to synchronize semantics, define unique features, review current regulatory procedures and describe novel applications that enable precision medicine
Continuous manufacturing process monitoring of pharmaceutical solid dosage form: A case study
No full textContinuous Manufacturing (CM) of pharmaceutical drug products is a rather new approach within the pharmaceutical industry. In the presented paper, a GMP continuous wet granulation line used for clinical production of solid dosage forms was investigated with a thorough monitoring strategy regarding process performance and robustness. The line was composed of the subsequent continuous unit operations feeding – twin-screw wet-granulation – fluid-bed drying – sieving and tableting; the formulation of a new pharmaceutical entity in development was selected for this study. In detail, a Design of Experiments (DoE) was used to evaluate the impact of the three main factors (amount of water, filling rate, and shear force in twin-screw granulator) on the tablet quality. The process was monitored via in-process control (IPC) tests (e.g. weight, hardness, disintegration, and loss-on-drying), Process Analytical Technologies (PAT), and through the analysis of the process parameters (multivariate process control). The tested formulation was very robust to the large process variation of the DoE: all IPC results were in specification, the PAT probes provided stable results for the content uniformity and no critical variations can be detected in the process parameters. An adequate monitoring strategy was presented and the robustness of the process with one formulation has been demonstrated. In summary, this continuous process in combination with smart formulation development allows the robust production of constant quality tablets. The synergy between PAT, process data science and IPC creates an adequate monitoring framework of the continuous manufacturing line
Targeting RNA with Small Molecules: Identification of Selective, RNA-Binding Small Molecules Occupying Drug-Like Chemical Space.
No full textAlthough the potential value of RNA as a target for new small molecule therapeutics is becoming increasingly credible, the physicochemical properties required for small molecules to selectively bind to RNA remain relatively unexplored. To investigate the druggability of RNAs with small molecules, we have employed affinity mass spectrometry, using the Automated Ligand Identification System (ALIS), to screen 42 RNAs from a variety of RNA classes, each against an array of chemically diverse drug-like small molecules (~50,000 compounds) and functionally annotated tool compounds (~5100 compounds). The set of RNA-small molecule interactions that was generated was compared with that for protein-small molecule interactions, and naïve Bayesian models were constructed to determine the types of specific chemical properties that bias small molecules toward binding to RNA. This set of RNA-selective chemical features was then used to build an RNA-focused set of ~3800 small molecules that demonstrated increased propensity toward binding the RNA target set. In addition, the data provide an overview of the specific physicochemical properties that help to enable binding to potential RNA targets. This work has increased the understanding of the chemical properties that are involved in small molecule binding to RNA, and the methodology used here is generally applicable to RNA-focused drug discovery efforts
Leucine-rich repeat kinase 2 (LRRK2) inhibitors differentially modulate glutamate release and Serine935 LRRK2 phosphorylation in striatal and cerebrocortical synaptosomes
No full textMutations in leucine‐rich repeat kinase 2 (LRRK2) gene have been pathogenically linked to Parkinson's disease, and pharmacological inhibition of LRRK2 is being pursued to tackle nigro‐striatal dopaminergic neurodegeneration. However, LRRK2 kinase inhibitors may have manifold actions, affecting not only pathological mechanisms in dopaminergic neurons but also physiological functions in nondopaminergic neurons. Therefore, we investigated whether LRRK2 kinase inhibitors differentially modulate dopamine and glutamate release from the mouse striatum and cerebral cortex. Spontaneous and KCl‐evoked [3H]‐dopamine and glutamate release from superfused synaptosomes obtained from wild‐type and LRRK2 knock‐out, kinase‐dead or G2019S knock‐in mice was measured. Two structurally unrelated inhibitors, LRRK2‐IN‐1 and GSK2578215A, were tested. LRRK2, phosphoSerine1292 and phosphoSerine935 LRRK2 levels were measured in all genotypes, and target engagement was evaluated by monitoring phosphoSerine935 LRRK2. LRRK2‐IN‐1 inhibited striatal glutamate but not dopamine release; GSK2578215A inhibited striatal dopamine and cortical glutamate but enhanced striatal glutamate release. LRRK2‐IN‐1 reduced striatal and cortical phosphoSerine935 levels whereas GSK2578215A inhibited only the former. Neither LRRK2 inhibitor affected neurotransmitter release in LRRK2 knock‐out and kinase‐dead mice; however, they facilitated dopamine without affecting striatal glutamate in G2019S knock‐in mice. GSK2578215A inhibited cortical glutamate release in G2019S knock‐in mice. We conclude that LRRK2‐IN‐1 and GSK2578215A modulate exocytosis by blocking LRRK2 kinase activity, although their effects vary depending on the nerve terminal examined. The G2019S mutation unravels a dopamine‐promoting action of LRRK2 inhibitors while blunting their effects on glutamate release, which highlights their positive potential for the treatment of PD, especially of LRRK2 mutation carriers
Preclinical Evaluation of Benzazepine-Based PET Radioligands ( R)- and ( S)-11C-Me-NB1 Reveals Distinct Enantiomeric Binding Patterns and a Tightrope Walk Between GluN2B- and σ1-Receptor-Targeted PET Imaging
No full textOur understanding of the NMDA receptor subunit composition, localization and function has dramatically improved and has led to the identification of the GluN2B-subunit as a key contributor to excitotoxicity-induced apoptosis. GluN2B antagonists have failed to demonstrate clinical efficacy and more are currently under clinical development. A suitable GluN2B-selective PET radioligand, which would facilitate target occupancy studies using imaging modalities such as positron emission tomography is lacking.
We have recently reported on (rac)-[11C]Me-NB1, a GluN2B-specific probe with high affinity (Ki to human GluN1/GluN2B of 5.4 nM) and excellent pharmacokinetic properties. The present study demonstrates that the enantiomeric pure forms of [11C]Me-NB1 show entirely different behavior as illustrated by distinct binding patterns in autoradiographic studies with rodent brain tissues, molecular dynamics studies as well as in vivo dose-response experiments. Whereas, the R-enantiomer, (R)-[11C]Me-NB1 revealed high selectivity for the GluN2B-rich forebrain, the S-enantiomer, (S)-[11C]Me-NB1, displayed a homogenous distribution pattern in autoradiograms of rodent brain and was found to predominantly bind to the σ1 receptor. (R)-[11C]Me-NB1 revealed outstanding characteristics as a GluN2B PET imaging agent as evidenced by in vitro and ex vivo autoradiography as well as dose-response experiments in rodents. Receptor occupancy studies with CP101,606, the only GluN2B-antagonist with well-documented clinical efficacy, showed that the currently applied therapeutic dose of 200 ng/mL exhibits 80 % receptor occupancy, demonstrating the utility of (R)-[11C]Me-NB1 for in vivo drug occupancy studies.. Finally, we validated (R)-[11C]Me-NB1 on post-mortem human brain tissue sections and showed that (R)-[11C]Me-NB1 binds specifically to the GluN2B-subunit of the NMDA receptor in humans
Biased Complement Diversity Selection for Effective Exploration of Chemical Space in Hit-Finding Campaigns.
No full textThe success of hit-finding campaigns relies on many factors, including the quality and diversity of the set of compounds that is selected for screening. This paper presents a generalized workflow that guides compound selections from large compound archives with opportunities to bias the selections with available knowledge in order to improve hit quality while still effectively sampling the accessible chemical space. An optional flag in the workflow supports an explicit complement design function where diversity selections complement a given core set of compounds. Results from three project applications as well as a literature case study exemplify the effectiveness of the approach, which is available as a KNIME workflow named Biased Complement Diversity (BCD)