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This year's review on bioactivation and reactivity began as a part of the annual review on biotransformation and bioactivation led by Cyrus Khojasteh (see references). Increased contributions from experts in the field led to the development of a stand alone edition for the first time this year focused specifically on bioactivation and reactivity. Our objective for this review is to highlight and share articles which we deem influential and significant regarding the development of covalent inhibitors, mechanisms of reactive metabolite formation, enzyme inactivation, and drug safety. Based on the selected articles, we created two sections: (1) reactivity and enzyme inactivation, and (2) bioactivation mechanisms and safety (Table 1). Several biotransformation experts have contributed to this effort from academic and industry settings.[Table: see text].

Biotransformation field is constantly evolving with new molecular structures and discoveries of metabolic pathways that impact efficacy and safety. Recent review by Kramlinger et al. (2022) nicely captures the future (and the past) of highly impactful science of biotransformation (see the first article). Based on the selected articles, this review was categorized into three sections: (1) new modalities biotransformation, (2) drug discovery biotransformation, and (3) drug development biotransformation (Table 1).

Although intestinal metabolism plays an important role in drug disposition, early predictions of human outcomes are challenging, in part because of limitations of available in vitro models. To address this, we have evaluated three in vitro models of human intestine (microsomes, permeabilized enterocytes, and cryopreserved intestinal mucosal epithelium) as tools to assess intestinal metabolism and estimate the fraction escaping gut metabolism (fg) in drug discovery. The models were tested with a chemically diverse set of 32 compounds, including substrates for oxidoreductive, hydrolytic, and conjugative enzymes. Liquid chromatography–high-resolution mass spectrometry was used to quantify substrate disappearance [intrinsic clearance (CLint)] and qualify metabolite formation (quantitative-qualitative bioanalysis). Fraction unbound in the incubation (fu,inc) was determined by rapid equilibrium dialysis. Measured in vitro results (CLint and fu,inc) were supplemented with literature data [passive Caco-2 apical to basolateral permeability, enterocyte blood flow, and intestinal surface area (A)] and combined using a midazolam-calibrated Qgut model to predict human fg values. All three models showed reliable CYP and UDP-glucuronosyltransferase activities, but enterocytes and mucosa may offer advantages for low-clearance compounds and alternative pathways (e.g., sulfation, hydrolases, and flavin-containing monooxigenases). Early predictions of human fg values were acceptable for the high-fg compounds (arbitrarily fg > 0.7). However, predictions of low- and moderate-fg values (arbitrarily fg Significance Statement We found that cellular models of the human gut (permeabilized enterocytes and cryopreserved intestinal mucosa) offer an alternative to and potential advantage over intestinal microsomes in studies of drug metabolism, particularly for low-clearance compounds and alternative pathways (e.g., sulfation, hydrolases, and flavin-containing monooxigenases). The predictivity of human fraction escaping gut metabolism for common CYP and UDP-glucuronosyltransferase substrates based on the Qgut model is still limited, however, and appropriate further evaluation is recommended.

Unlike with new chemical entities, the biotransformation of therapeutic proteins (TPs) has not been routinely investigated or included in regulatory filings. Nevertheless, there is an expanding pool of evidence suggesting that a more in-depth understanding of biotransformation could better aid the discovery and development of increasingly diverse modalities. For instance, such biotransformation analysis of TPs affords important information on molecular stability, which in turn may shed light on any potential impact on binding affinity, potency, pharmacokinetics, efficacy, safety, or bioanalysis. This perspective summarizes the current practices in studying biotransformation of TPs and related findings in the biopharmaceutical industry. Various TP case studies are discussed, and a fit-for-purpose approach is recommended when investigating their biotransformation. In addition, we provide a decision tree to guide the biotransformation characterization for selected modalities. By raising the awareness of this important topic, which remains relatively underexplored in the development of TPs (Bolleddula et al., 2022), we hope that current and developing practices can pave the way for establishing a consensus on the biotransformation assessment of TPs. SIGNIFICANCE STATEMENT: This article provides a comprehensive perspective of the current practices for exploring the biotransformation of therapeutic proteins across the drug development industry. We, the participants of the Innovation and Quality therapeutic protein absorption distribution metabolism excretion working group, recommend and summarize appropriate approaches for conducting biotransformation studies to support internal decision making based on the data generated in discovery and development.

Snow-layer classification is an essential diagnostic task for a wide variety of cryospheric science and climate research applications. Traditionally, these measurements are made in snow pits, requiring trained operators and a substantial time commitment. The SnowMicroPen (SMP), a portable high-resolution snow penetrometer, has been demonstrated as a capable tool for rapid snow grain classification and layer type segmentation through statistical inversion of its mechanical signal. The manual classification of the SMP profiles requires time and training and becomes infeasible for large datasets.Here, we introduce a novel set of SMP measurements collected during the MOSAiC expedition and apply Machine Learning (ML) algorithms to automatically classify and segment SMP profiles of snow on Arctic sea ice. To this end, different supervised and unsupervised ML methods, including Random Forests, Support Vector Machines, Artificial Neural Networks, and k-means Clustering, are compared. A subsequent segmentation of the classified data results in distinct layers and snow grain markers for the SMP profiles. The models are trained with the dataset by King et al. (2020) and the MOSAiC SMP dataset. The MOSAiC dataset is a unique and extensive dataset characterizing seasonal and spatial variation of snow on the central Arctic sea-ice.We will test and compare the different algorithms and evaluate the algorithms’ effectiveness based on the need for initial dataset labeling, execution speed, and ease of implementation. In particular, we will compare supervised to unsupervised methods, which are distinguished by their need for labeled training data.The implementation of different ML algorithms for SMP profile classification could provide a fast and automatic grain type classification and snow layer segmentation. Based on the gained knowledge from the algorithms’ comparison, a tool can be built to provide scientists from different fields with an immediate SMP profile classification and segmentation. King, J., Howell, S., Brady, M., Toose, P., Derksen, C., Haas, C., & Beckers, J. (2020). Local-scale variability of snow density on Arctic sea ice. The Cryosphere, 14(12), 4323-4339, https://doi.org/10.5194/tc-14-4323-2020.

Background: The pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) might be curtailed by vaccination. We assessed the safety, reactogenicity, and immunogenicity of a viral vectored coronavirus vaccine that expresses the spike protein of SARS-CoV-2. Methods: We did a phase 1/2, single-blind, randomised controlled trial in five trial sites in the UK of a chimpanzee adenovirus-vectored vaccine (ChAdOx1 nCoV-19) expressing the SARS-CoV-2 spike protein compared with a meningococcal conjugate vaccine (MenACWY) as control. Healthy adults aged 18–55 years with no history of laboratory confirmed SARS-CoV-2 infection or of COVID-19-like symptoms were randomly assigned (1:1) to receive ChAdOx1 nCoV-19 at a dose of 5 × 10 10 viral particles or MenACWY as a single intramuscular injection. A protocol amendment in two of the five sites allowed prophylactic paracetamol to be administered before vaccination. Ten participants assigned to a non-randomised, unblinded ChAdOx1 nCoV-19 prime-boost group received a two-dose schedule, with the booster vaccine administered 28 days after the first dose. Humoral responses at baseline and following vaccination were assessed using a standardised total IgG ELISA against trimeric SARS-CoV-2 spike protein, a muliplexed immunoassay, three live SARS-CoV-2 neutralisation assays (a 50% plaque reduction neutralisation assay [PRNT 50]; a microneutralisation assay [MNA 50, MNA 80, and MNA 90]; and Marburg VN), and a pseudovirus neutralisation assay. Cellular responses were assessed using an ex-vivo interferon-γ enzyme-linked immunospot assay. The co-primary outcomes are to assess efficacy, as measured by cases of symptomatic virologically confirmed COVID-19, and safety, as measured by the occurrence of serious adverse events. Analyses were done by group allocation in participants who received the vaccine. Safety was assessed over 28 days after vaccination. Here, we report the preliminary findings on safety, reactogenicity, and cellular and humoral immune responses. The study is ongoing, and was registered at ISRCTN, 15281137, and ClinicalTrials.gov, NCT04324606. Findings: Between April 23 and May 21, 2020, 1077 participants were enrolled and assigned to receive either ChAdOx1 nCoV-19 (n=543) or MenACWY (n=534), ten of whom were enrolled in the non-randomised ChAdOx1 nCoV-19 prime-boost group. Local and systemic reactions were more common in the ChAdOx1 nCoV-19 group and many were reduced by use of prophylactic paracetamol, including pain, feeling feverish, chills, muscle ache, headache, and malaise (all p80 and in 35 (100%) participants when measured in PRNT 50. After a booster dose, all participants had neutralising activity (nine of nine in MNA 80 at day 42 and ten of ten in Marburg VN on day 56). Neutralising antibody responses correlated strongly with antibody levels measured by ELISA (R 2=0·67 by Marburg VN; p

Aldehyde oxidase (AO) catalyzes oxidations of azaheterocycles and aldehydes, amide hydrolysis, and diverse reductions. AO substrates are rare among marketed drugs, and many candidates failed due to poor pharmacokinetics, interspecies differences, and adverse effects. As most issues arise from complex and poorly understood AO biology, an effective solution is to stop or decrease AO metabolism. This perspective focuses on rational drug design approaches to modulate AO-mediated metabolism in drug discovery. AO biological aspects are also covered, as they are complementary to chemical design and important when selecting the experimental system for risk assessment. The authors' recommendation is an early consideration of AO-mediated metabolism supported by computational and in vitro experimental methods but not an automatic avoidance of AO structural flags, many of which are versatile and valuable building blocks. Preferably, consideration of AO-mediated metabolism should be part of the multiparametric drug optimization process, with the goal to improve overall drug-like properties.

After graduating with an Oceanography degree from Swansea University, Lloyd has spent over 20 years in the field of bioanalysis and metabolite profiling. He started his career in large pharma at Wyeth UK, where he was involved in setting up the first GC and LC–MS/MS systems for both QC and early DMPK assays, employing EI/CI, thermospray, and the then new electrospray ionization techniques. Lloyd then joined Celltech, now UCB, where he is primarily tasked with metabolite profiling by LC–MS and NMR to support both early research projects and late-stage clinical studies. The application of liquid chromatography high-resolution mass spectrometry for simultaneous quantitative and qualitative (quan/qual) analysis has gained momentum across a range of different scientific arenas in recent years. The ability to acquire high quality quantitative data, whilst also capturing qualitative data for either parallel or retrospective analysis, is a powerful resource, especially in view of ever-reducing cycle times, laboratory space and budgets. The quan/qual approach employing a Q-Exactive™ Orbitrap high-resolution mass spectrometer has been successfully introduced into UCB's research DMPK department. This article describes our experiences in introducing quan/qual, issues that we discovered in establishing this new working paradigm, the evolution of the strategy and its future potential.

The 2016 10th Workshop on Recent Issues in Bioanalysis (10th WRIB) took place in Orlando, Florida with participation of close to 700 professionals from pharmaceutical/biopharmaceutical companies, biotechnology companies, contract research organizations, and regulatory agencies worldwide. WRIB was once again a 5-day, weeklong event – A Full Immersion Week of Bioanalysis including Biomarkers and Immunogenicity. As usual, it was specifically designed to facilitate sharing, reviewing, discussing and agreeing on approaches to address the most current issues of interest including both small and large molecule analysis involving LCMS, hybrid LBA/LCMS, and LBA approaches, with the focus on biomarkers and immunogenicity. This 2016 White Paper encompasses recommendations emerging from the extensive discussions held during the workshop, and is aimed to provide the bioanalytical community with key information and practical solutions on topics and issues addressed, in an effort to enable advances in scientific excellence, improved quality and better regulatory compliance. This white paper is published in 3 parts due to length. This part (Part 1) discusses the recommendations for small molecules, peptides and small molecule biomarkers by LCMS. Part 2 (Hybrid LBA/LCMS and regulatory inputs from major global health authorities) and Part 3 (large molecule bioanalysis using LBA, biomarkers and immunogenicity) will be published in the Bioanalysis journal, issue 23.

CD4+CD25hi FOXP3+ regulatory T cells (Tregs) maintain tolerance to self-Ags. Their defective function is involved in the pathogenesis of multiple sclerosis (MS), an inflammatory demyelinating disease of the CNS. However, the mechanisms of such defective function are poorly understood. Recently, we reported that stimulation of TLR2, which is preferentially expressed by human Tregs, reduces their suppressive function and skews them into a Th17-like phenotype. In this study, we tested the hypothesis that TLR2 activation is involved in reduced Treg function in MS. We found that Tregs from MS patients expressed higher levels of TLR2 compared with healthy controls, and stimulation with the synthetic lipopeptide Pam3Cys, an agonist of TLR1/2, reduced Treg function and induced Th17 skewing in MS patient samples more than in healthy controls. These data provide a novel mechanism underlying diminished Treg function in MS. Infections that activate TLR2 in vivo (specifically through TLR1/2 heterodimers) could shift the Treg/Th17 balance toward a proinflammatory state in MS, thereby promoting disease activity and progression.

A series of 4-azaindole inhibitors of c-Met kinase is described. The postulated binding mode was confirmed by an X-ray crystal structure and series optimisation was performed on the basis of this structure. Future directions for series development are discussed.

Data from a group of 538 placebo-treated neurotic outpatients who had participated in drug trials involving both anti-anxiety and antidepressant agents were analyzed in an effort to identify characteristics associated with failure to adhere to prescribed placebo dosage and with failure to complete a 4 week treatment program. The total patient sample contained 302 Completers, 74 Deviators, and 162 Dropouts. Adherence to treatment protocol was more frequent in private practice than in clinic patients and in patients more favorably positioned with regard to social status, stability, and advantage. It was argued that Treatment Setting differences are due in part to differences between clinic and private practice patients in socio-economic level and to both patient and physician attitudes engendered by this difference. The frequency of adherence to protocol was unrelated to social status within treatment settings. Employed patients tended to adhere more closely to protocol than unemployed patients, irrespective of the setting in which they received treatment and irrespective of their socio-economic level. Finally, adherence to protocol was more common in patients who had received more limited amounts of previous drug treatment. Dropping out of treatment was more likely to occur in patients who experienced high levels of insomia in a symptom context dominated by anxiety rather than depression. Treatment response in Dropouts was less positive than that of either Deviators or Completers. There was also some indication that patients who drop out from placebo treatment tend to be younger than those who do not. Patients who deviated from prescribed placebo dosage, but who completed a full 4 week course of treatment, were less well liked by their treating physicians, but were also evaluated as less hostile and less irritable than were patients in the other 2 treatment status groups. Evidence was presented that hostility level and physician liking for the patient play contrasting roles in the Completer and Deviator groups. The implications of these findings for both the practitioner and the researcher were briefly considered.