Annual review of pharmacology and toxicology最新文献

Thalidomide and its derivatives are powerful cancer therapeutics that are among the best-understood molecular glue degraders (MGDs). These drugs selectively reprogram the E3 ubiquitin ligase cereblon (CRBN) to commit target proteins for degradation by the ubiquitin-proteasome system. MGDs create novel recognition interfaces on the surface of the E3 ligase that engage in induced protein-protein interactions with neosubstrates. Molecular insight into their mechanism of action opens exciting opportunities to engage a plethora of targets through a specific recognition motif, the G-loop. Our analysis shows that current CRBN-based MGDs can in principle recognize over 2,500 proteins in the human proteome that contain a G-loop. We review recent advances in tuning the specificity between CRBN and its MGD-induced neosubstrates and deduce a set of simple rules that govern these interactions. We conclude that rational MGD design efforts will enable selective degradation of many more proteins, expanding this therapeutic modality to more disease areas.

Today's challenge for precision medicine involves the integration of the impact of molecular clocks on drug pharmacokinetics, toxicity, and efficacy toward personalized chronotherapy. Meaningful improvements of tolerability and/or efficacy of medications through proper administration timing have been confirmed over the past decade for immunotherapy and chemotherapy against cancer, as well as for commonly used pharmacological agents in cardiovascular, metabolic, inflammatory, and neurological conditions. Experimental and human studies have recently revealed sexually dimorphic circadian drug responses. Dedicated randomized clinical trials should now aim to issue personalized circadian timing recommendations for daily medical practice, integrating innovative technologies for remote longitudinal monitoring of circadian metrics, statistical prediction of molecular clock function from single-timepoint biopsies, and multiscale biorhythmic mathematical modelling. Importantly, chronofit patients with a robust circadian function, who would benefit most from personalized chronotherapy, need to be identified. Conversely, nonchronofit patients could benefit from the emerging pharmacological class of chronobiotics targeting the circadian clock.

Direct oral anticoagulants (DOACs) have largely replaced vitamin K antagonists, mostly warfarin, for the main indications for oral anticoagulation, prevention and treatment of venous thromboembolism, and prevention of embolic stroke in atrial fibrillation. While DOACs offer practical, fixed-dose anticoagulation in many patients, specific restrictions or contraindications may apply. DOACs are not sufficiently effective in high-thrombotic risk conditions such as antiphospholipid syndrome and mechanical heart valves. Patients with cancer-associated thrombosis may benefit from DOACs, but the bleeding risk, particularly in those with gastrointestinal or urogenital tumors, must be carefully weighed. In patients with frailty, excess body weight, and/or moderate-to-severe chronic kidney disease, DOACs must be cautiously administered and may require laboratory monitoring. Reversal agents have been developed and approved for life-threatening bleeding. In addition, the clinical testing of potentially safer anticoagulants such as factor XI(a) inhibitors is important to further optimize anticoagulant therapy in an increasingly elderly and frail population worldwide.

Drug discovery is adapting to novel technologies such as data science, informatics, and artificial intelligence (AI) to accelerate effective treatment development while reducing costs and animal experiments. AI is transforming drug discovery, as indicated by increasing interest from investors, industrial and academic scientists, and legislators. Successful drug discovery requires optimizing properties related to pharmacodynamics, pharmacokinetics, and clinical outcomes. This review discusses the use of AI in the three pillars of drug discovery: diseases, targets, and therapeutic modalities, with a focus on small-molecule drugs. AI technologies, such as generative chemistry, machine learning, and multiproperty optimization, have enabled several compounds to enter clinical trials. The scientific community must carefully vet known information to address the reproducibility crisis. The full potential of AI in drug discovery can only be realized with sufficient ground truth and appropriate human intervention at later pipeline stages.

Each year over half a million people experience permanent hearing loss caused by treatment with therapeutic drugs with ototoxic side effects. There is a major unmet clinical need for therapies that protect against this hearing loss without reducing the therapeutic efficacy of these lifesaving drugs. At least 17 clinical trials evaluating 10 therapeutics are currently underway for therapies aimed at preventing aminoglycoside- and/or cisplatin-induced ototoxicity. This review describes the preclinical and clinical development of each of these approaches, provides updates on the status of ongoing trials, and highlights the importance of appropriate outcome measures in trial design and the value of reporting criteria in the dissemination of results.

Lipoprotein(a) [Lp(a)] is a molecule bound to apolipoprotein(a) with some similarity to low-density lipoprotein cholesterol (LDL-C), which has been found to be a risk factor for cardiovascular disease (CVD). Lp(a) appears to induce inflammation, atherogenesis, and thrombosis. Approximately 20% of the world's population has increased Lp(a) levels, determined predominantly by genetics. Current clinical practices for the management of dyslipidemia are ineffective in lowering Lp(a) levels. Evolving RNA-based therapeutics, such as the antisense oligonucleotide pelacarsen and small interfering RNA olpasiran, have shown promising results in reducing Lp(a) levels. Phase III pivotal cardiovascular outcome trials [Lp(a)HORIZON and OCEAN(a)] are ongoing to evaluate their efficacy in secondary prevention of major cardiovascular events in patients with elevated Lp(a). The future of cardiovascular residual risk reduction may transition to a personalized approach where further lowering of either LDL-C, triglycerides, or Lp(a) is selected after high-intensity statin therapy based on the individual risk profile and preferences of each patient.

Sleep is essential for human well-being, yet the quality and quantity of sleep reduce as age advances. Older persons (>65 years old) are more at risk of disorders accompanied and/or exacerbated by poor sleep. Furthermore, evidence supports a bidirectional relationship between disrupted sleep and Alzheimer's disease (AD) or related dementias. Orexin/hypocretin neuropeptides stabilize wakefulness, and several orexin receptor antagonists (ORAs) are approved for the treatment of insomnia in adults. Dysregulation of the orexin system occurs in aging and AD, positioning ORAs as advantageous for these populations. Indeed, several clinical studies indicate that ORAs are efficacious hypnotics in older persons and dementia patients and, as in adults, are generally well tolerated. ORAs are likely to be more effective when administered early in sleep/wake dysregulation to reestablish good sleep/wake-related behaviors and reduce the accumulation of dementia-associated proteinopathic substrates. Improving sleep in aging and dementia represents a tremendous opportunity to benefit patients, caregivers, and health systems.

Interindividual variability in genes encoding drug-metabolizing enzymes, transporters, receptors, and human leukocyte antigens has a major impact on a patient's response to drugs with regard to efficacy and safety. Enabled by both technological and conceptual advances, the field of pharmacogenomics is developing rapidly. Major progress in omics profiling methods has enabled novel genotypic and phenotypic characterization of patients and biobanks. These developments are paralleled by advances in machine learning, which have allowed us to parse the immense wealth of data and establish novel genetic markers and polygenic models for drug selection and dosing. Pharmacogenomics has recently become more widespread in clinical practice to personalize treatment and to develop new drugs tailored to specific patient populations. In this review, we provide an overview of the latest developments in the field and discuss the way forward, including how to address the missing heritability, develop novel polygenic models, and further improve the clinical implementation of pharmacogenomics.

Seizures and other forms of neurovolatility are emerging as druggable prodromal mechanisms that link traumatic brain injury (TBI) to the progression of later dementias. TBI neurotrauma has both acute and long-term impacts on health, and TBI is a leading risk factor for dementias, including chronic traumatic encephalopathy and Alzheimer's disease. Treatment of TBI already considers acute management of posttraumatic seizures and epilepsy, and impressive efforts have optimized regimens of antiepileptic drugs (AEDs) toward that goal. Here we consider that expanding these management strategies could determine which AED regimens best prevent dementia progression in TBI patients. Challenges with this prophylactic strategy include the potential consequences of prolonged AED treatment and that a large subset of patients are refractory to available AEDs. Addressing these challenges is warranted because the management of seizure activity following TBI offers a rare opportunity to prevent the onset or progression of devastating dementias.

The reviews in Volume 64 of the Annual Review of Pharmacology and Toxicology cover diverse topics. A common theme in many of the reviews is the interindividual variability in the clinical response to drugs. Highlighted areas include emerging developments in pharmacogenomics that can predict the personal risk for drug inefficacy and/or adverse drug reactions. Other reviews focus on the use of circulating biomarkers to define drug metabolism phenotypes and the effect of circadian regulation on drug response. Another emerging technology, digital twins that model individual patients, is used to generate computational simulations of drug effects and identify optimal personalized treatments. Another variable that may affect clinical outcomes, the nocebo response (an adverse reaction to a placebo), complicates clinical trials. These reviews further document that pharmacological individuality is an essential component of the concepts of personalized medicine and precision medicine and will likely have an important impact on patient care.