Objective: We aimed to evaluate alirocumab- and evolocumab-related adverse events (AEs) in real-world compared with all other drugs, overall and by gender and age subgroups; we also aimed to compare their risks of cognitive impairment, musculoskeletal disorders and diabetes with various statins and ezetimibe.Methods: We retrospectively extracted AE reports from the FDA Adverse Event Reporting System (FAERS) database during July 2015-June 2021. Disproportionality analyses were performed using reporting odds ratios (RORs) to detect AE signals of alirocumab and evolocumab in the overall population and in different age and gender subgroups, respectively.Results: Compared with all other drugs, both alirocumab and evolocumab had a significant signal in “musculoskeletal and connective tissue disorders” (ROR₁ = 2.626, 95% CI 2.552–2.702; ROR2 = 2.575, 95% CI 2.538–2.613). The highest ROR value of 2.311 (95% CI 2.272–2.351) was for “injury, poisoning and procedural complications” and was found in patients aged ≥65 years on evolocumab. The most frequent AEs were “general disorders and administration site conditions” and “musculoskeletal and connective tissue disorders” for all subpopulations. At the preferred term level, the most frequent AE signal was myalgia for alirocumab and injection site pain for evolocumab, overall and by subgroups. Compared with statins/ezetimibe, PCSK9 inhibitors exhibited lower ROR values for adverse events associated with SOC “nervous system disorders”, “psychiatric disorders” and “metabolism and nutrition disorders” (all RORs < 1), but mixed results for musculoskeletal disorders. Compared with all other drugs, undocumented AEs, such as acute cardiac event (ROR = 30.0, 95% CI 9.4–95.3) and xanthoma (ROR = 9.3, 95% CI 3.4–25.5), were also reported.Conclusion: Real-world evidence showed that PCSK9 inhibitors were associated with an increased risk of musculoskeletal and connective tissue disorders and general disorders and administration site conditions, overall and by subgroups. Muscle toxicity, injection site reactions, and influenza-like illness were significant AE signals. Compared with various statins and ezetimibe, PCSK9 inhibitors have shown a favorable safety profile in muscle-related events, cognitive impairment and diabetes. Some undocumented AE signals were also reported. Due to the limitations of spontaneous reporting databases, further studies are still needed to establish causality and validate our results.

The outbreak and spread of coronavirus disease 2019 (COVID-19) highlighted the importance and urgency of the research and development of therapeutic drugs. Very early into the COVID-19 pandemic, China has begun developing drugs, with some notable progress. Herein, we summarizes the anti-COVID-19 drugs and promising drug candidates originally developed and researched in China. Furthermore, we discussed the developmental prospects, mechanisms of action, and advantages and disadvantages of the anti-COVID-19 drugs in development, with the aim to contribute to the rational use of drugs in COVID-19 treatment and more effective development of new drugs against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the variants. Neutralizing antibody is an effective approach to overcome COVID-19. However, drug resistance induced by rapid virus mutation will likely to challenge neutralizing antibodies. Taking into account current epidemic trends, small molecule drugs have a crucial role in fighting COVID-19 due to their significant advantage of convenient administration and affordable and broad-spectrum. Traditional Chinese medicines, including natural products and traditional Chinese medicine prescriptions, contribute to the treatment of COVID-19 due to their unique mechanism of action. Currently, the research and development of Chinese anti-COVID-19 drugs have led to some promising achievements, thus prompting us to expect even more rapidly available solutions.

Drug-induced liver injury (DILI) is a major cause of the withdrawal of pre-marketed drugs, typically attributed to oxidative stress, mitochondrial damage, disrupted bile acid homeostasis, and innate immune-related inflammation. DILI can be divided into intrinsic and idiosyncratic DILI with cholestatic liver injury as an important manifestation. The diagnosis of DILI remains a challenge today and relies on clinical judgment and knowledge of the insulting agent. Early prediction of hepatotoxicity is an important but still unfulfilled component of drug development. In response, in silico modeling has shown good potential to fill the missing puzzle. Computer algorithms, with machine learning and artificial intelligence as a representative, can be established to initiate a reaction on the given condition to predict DILI. DILIsym is a mechanistic approach that integrates physiologically based pharmacokinetic modeling with the mechanisms of hepatoxicity and has gained increasing popularity for DILI prediction. This article reviews existing in silico approaches utilized to predict DILI risks in clinical medication and provides an overview of the underlying principles and related practical applications.

Schizandrol A (SZA) and schizandrol B (SZB) are two active ingredients of Wuzhi capsule (WZC), a Chinese proprietary medicine commonly prescribed to alleviate tacrolimus (FK-506)-induced hepatoxicity in China. Due to their inhibitory effects on cytochrome P450 (CYP) 3A enzymes, SZA/SZB may display drug–drug interaction (DDI) with tacrolimus. To identify the extent of this DDI, the enzymes’ inhibitory profiles, including a 50% inhibitory concentration (IC₅₀) shift, reversible inhibition (RI) and time-dependent inhibition (TDI) were examined with pooled human-liver microsomes (HLMs) and CYP3A5-genotyped HLMs. Subsequently, the acquired parameters were integrated into a physiologically based pharmacokinetic (PBPK) model to quantify the interactions between the SZA/SZB and the tacrolimus. The metabolic studies indicated that the SZB displayed both RI and TDI on CYP3A4 and CYP3A5, while the SZA only exhibited TDI on CYP3A4 to a limited extent. Moreover, our PBPK model predicted that multiple doses of SZB would increase tacrolimus exposure by 26% and 57% in CYP3A5 expressers and non-expressers, respectively. Clearly, PBPK modeling has emerged as a powerful approach to examine herb-involved DDI, and special attention should be paid to the combined use of WZC and tacrolimus in clinical practice.

As third-generation tyrosine kinase inhibitors, furmonertinib and osimertinib exhibit better efficacy than first and second generation TKIs in patients with advanced non-small-cell lung cancer. However, radioactive pharmacokinetics studies showed that parent-related components remain in human plasma for at least 21 days after oral administration. Similar pharmacokinetic profiles were found in pyrotinib and neratinib, which have been identified to covalently bind with human serum albumin at Lys-190, leading to low extraction recovery in protein precipitation. However, the binding mechanism of Furmonertinib and Osimertinib in human plasma has not been confirmed. Comprehensive techniques were used to investigate the mechanism of this binding, including UHPLC coupled with HRMS and online/offline radioactivity profiling. SDS-PAGE and further autoradiography were also used to detect drug-protein adducts. We found that most furmonertinib exists in the human plasma following ex vivo incubation in the form of protein-drug adducts. Only lysine-furmonertinb adducts were found in pronase digests. A standard reference of lysine-furmonertinib was synthesized and confirmed by NMR. Through peptide mapping analysis, we confirmed that furmonertinib almost exclusively binds with HSA in plasma following ex vivo incubation, via Michael addition at Lys-195 and Lys-199, instead of Lys-190. Two peptides found to bond with furmonertinib were ASSAKQR and LKCASLQK. Osimertinib was also found to bond with Lys-195 and Lys-199 of HSA via peptide mapping analysis. Significance Statement Here we report, that furmonertinib and osimertinib can covalently bind with human serum albumin at the site of Lys-195 and Lys-199 instead of Lys -190, leading to the long duration of drug-protein adducts in the human body.

Pharmacokinetic characterization plays a vital role in drug discovery and development. Although involving numerous laboratory animals with error-prone, labor-intensive, and time-consuming procedures, pharmacokinetic profiling is still irreplaceable in preclinical studies. With physiologically based pharmacokinetic (PBPK) modeling, the in vivo profiles of drug absorption, distribution, metabolism, and excretion can be predicted. To evaluate the application of such an approach in preclinical investigations, the plasma pharmacokinetic profiles of seven commonly used probe substrates of microsomal enzymes, including phenacetin, tolbutamide, omeprazole, metoprolol, chlorzoxazone, nifedipine, and baicalein, were predicted in rats using bottom-up PBPK models built with in vitro data alone. The prediction’s reliability was assessed by comparison with in vivo pharmacokinetic data reported in the literature. The overall predicted accuracy of PBPK models was good with most fold errors within 2, and the coefficient of determination (R²) between the predicted concentration data and the observed ones was more than 0.8. Moreover, most of the observation dots were within the prediction span of the sensitivity analysis. We conclude that PBPK modeling with acceptable accuracy may be incorporated into preclinical studies to refine in vivo investigations, and PBPK modeling is a feasible strategy to practice the principles of 3Rs.