Current Neuropharmacology - Volume 24, Issue 1, 2026

In the medicinal chemistry (MC) field, artificial intelligence (AI) has been used to establish quantitative structure-activity relationship (QSAR) classification models, virtual screening, drug discovery, drug design, and so on. In this investigation, MC AI studies (AI-MC) (from 2001-2023) underwent quantitative and qualitative modeling analyses.

Using a hybrid research strategy incorporating content analyses and bibliometric methods, we retrospectively analysed the AI-MC literature using a bibliometrix package (R software) combined with CiteSpace V and VOSviewer programs.

Between 2001 and 2023, AI-MC articles were published in 92 countries or regions, with China and the United States leading in the number of publications. Also, 196 affiliations were added to AI-MC research; the CHINESE ACADEMY OF SCIENCES contributed the most. Reference clusters were categorized as follows: (1) QSAR, (2) virtual screening, (3) drug discovery, (4) drug design. Predictive model (2020-2021), molecular fingerprints (2021-2023) and scoring function (2021-2023) reflected research frontier keywords. As we look to the future, the ongoing progress and innovation in technology herald the promising development of multimodal and large language models (LLMs) within the realm of MC.

The integration of AI into MC has significantly transformed the landscape of drug development. AI techniques, particularly machine learning, and deep learning algorithms, have demonstrated remarkable potential in accelerating the discovery and optimization of new drugs. By leveraging large datasets and advanced computational models, AI enhances the efficiency of virtual screening, improves the accuracy of QSAR models, and facilitates the design of novel therapeutic agents. As the technology continues to advance, the development of multimodal and large language models (LLMs) is expected to further revolutionize this field, offering new opportunities for more precise and efficient drug design and discovery.

We comprehensively characterized the AI-MC field and determined future trends and hotspots. Importantly, we provided a dynamic oversight of the AI-MC literature and identified key upcoming research areas.

Polyglutamine (polyQ) spinocerebellar ataxias (SCA) are a group of autosomal dominant neurodegenerative disorders for which no effective treatments currently exist. These conditions impose a significant burden on patients, their families, and society. Consequently, the treatment of these disorders has attracted significant global interest.

We conducted this bibliometric analysis to identify the key research hotspots and predict the future research directions of this field.

Studies relating to the treatment of polyQ SCA published from 1999 to 2024 were retrieved from the Web of Science Core Collection database. Relevant papers were selected using predefined inclusion and exclusion criteria. HistCite, VOSviewer, CiteSpace, and alluvial generator were used in the bibliometric analysis.

Overall, 935 papers were included. The number of publications in this field showed a trend toward a fluctuating increase. The United States and the University of Coimbra were the leading countries and institutions, respectively, in terms of publication number. The two most productive and highly cited authors were Luis Pereira de Almeida and Patricia Maciel. The journals Cerebellum, Human Molecular Genetics, and Movement Disorders were considered the most influential based on the number of publications and citations. Furthermore, “new SCA types”, “Huntington’s disease”, “clinical trial”, “gene therapy”, “disease models,” and “Aggregation clearance therapy” emerged as current hotspots in this field, as revealed by the reference and keyword analyses.

This study presents a systematic bibliometric analysis of research on the polyQ SCA treatment, which we hope will assist researchers in identifying the key topics and future research directions in this field.

Parkinson’s disease (PD) is often associated with depression, which poses an additional burden for patients and their families. However, evidence regarding the optimal treatment for depression in PD remains limited, with insufficient data supporting the efficacy of most antidepressant drugs.

The primary objective of this pilot, prospective, open-label, single-arm study was to analyze the safety and tolerability of vortioxetine drops on depressive symptoms in PD patients over 16 weeks of treatment. The secondary objective was to study vortioxetine's effectiveness on depression.

Sixteen out of 20 PD patients who completed the study demonstrated that the treatment was safe and well tolerated; no change in PD symptom severity, abnormality of clinical parameters, body weight, or ECG emerged. The most common side effect was nausea. Depressive symptoms rated by the Beck Depression Inventory and the Hamilton Depression Rating Scale score (HAM-D-17) showed a significant improvement at the end of the study period without a worsening of motor functions, as measured by UPDRS part III. The majority of patients also reported an improvement in depressive symptoms measured by the Patient Global Impression of Improvement scale.

Vortioxetine is a safe and well-tolerated therapeutic approach for depression in Parkinson’s disease. As a secondary objective, an improvement in depressive symptoms was observed. However, the study’s open-label design and small sample size limit the generalizability of the findings.

NCT04301492.

Numerous studies have demonstrated that efgartigimod is effective in treating myasthenia gravis (MG) across various patient populations. However, there is limited evidence regarding its use in patients with new-onset acetylcholine receptor antibody-positive generalized MG (AChR-gMG). Therefore, this study aimed to investigate the real-world safety and effectiveness of efgartigimod in Chinese patients with new-onset anti-cholinergic receptor (AChR)- gMG.

This prospective study was conducted in 29 patients with new-onset AChR-gMG, with a three-month follow-up. The Myasthenia Gravis Activities of Daily Living (MG-ADL) score, Quantitative Myasthenia Gravis score, prednisone dose, laboratory data, and adverse events were assessed at every follow-up visit.

At 4, 8, and 12 weeks, the mean change in MG-ADL scores was 8.13 ± 3.66, 7.41 ± 4.22, and 6.37 ± 4.67, respectively. Compared with the baseline, 96% (28/29) of patients achieved an MG-ADL response (defined as a decrease of ≥2 points), with a mean response time of 0.81 ± 0.53 weeks (5.67 ± 3.71 days). After one cycle, 52% (15/29) of patients achieved minimal symptom expression (MSE), while 41% maintained MSE at 12 weeks. Moreover, 89% and 72% of MG-ADL responders sustained for 8 and 12 consecutive weeks, respectively. Additionally, patients with thymomatous MG exhibited a poorer response to efgartigimod and required two infusion cycles. All patients were able to reduce their daily steroid dose, and the mean daily prednisone dose decreased by 10.73 mg per day. The treatment was well tolerated, and a few mild adverse events were reported.

These results demonstrate the clinical significance of efgartigimod in patients with new-onset AChR-gMG, achieving rapid symptom relief and steroid reduction. Additionally, the potential of efgartigimod to serve as a bridge treatment, facilitating a steady transition to long-term conventional immunosuppressive therapy, was demonstrated. Due to limitations in this study, such as a small sample size, larger randomized controlled trials are needed to validate.

Our study showed that efgartigimod is clinically beneficial and offers rapid symptom control in patients with new-onset AChR-gMG. A more aggressive application of efgartigimod in combination with corticosteroids may lead to a smoother therapeutic transition, which will further maintain favorable conditions.

Chronic insomnia disorder significantly affects cognitive, emotional, and physical health. Recently, the dual orexin receptor antagonist (DORA) daridorexant was approved for treating chronic insomnia in several countries. Given the limited evidence available, expert consensus was sought to clarify key clinical issues, inform practice, and guide future research.

Thirteen Italian sleep experts employed the Nominal Group Technique (NGT) to identify and rank important clinical questions. The process involved independent thought generation, group discussion, and online voting using a 5-point Likert scale.

The NGT process resulted in 55 statements across five key clinical questions, with relevance scores guiding their categorization into three tiers. Key findings highlight daridorexant’s mechanism of action, safety profile, efficacy on night and day parameters, and suitability for long-term use. The experts emphasized cross-tapering strategies for switching from other hypnotics, the importance of sleep psychoeducation, and using the Insomnia Severity Index and sleep diaries for treatment evaluation.

Daridorexant may address insomnia without increasing sedation via its dual orexin receptor antagonism. Daridorexant seems to be effective and safe even in special patient populations, such as the elderly and those with comorbid conditions (neurodegenerative disorders and cognitive impairment, comorbid insomnia and sleep apnea, psychiatric conditions and mood disorders, epilepsy, and restless leg syndrome), thus representing a new, promising option for insomnia treatment.

The expert consensus provides a comprehensive framework for daridorexant clinical application, advocating for further research to expand the evidence base and refine best practices, as well as underscoring the importance of a multidisciplinary approach that combines both pharmacological and psychosocial interventions to optimize outcomes.

Radiotherapy is one of the main therapeutic methods for tumors, and radiation-related cognitive impairment has attracted increasing attention. The purpose of this study was to explore the research prospects in the field of radiotherapy-associated cognitive decline through bibliometric analysis.

Literature on radiotherapy-related cognitive impairment published during 2004-2023 were extracted from the Web of Science Core Collection database. VOSviewer and R-bibliometrix were utilized to perform bibliometric analysis.

A total of 8,365 publications were retrieved from the database. The United States emerged as the leading country in this research field, with St. Jude Children's Research Hospital identified as the most productive institution. Thomas E. Merchant was the most prolific author in this field, while Charles L. Limoli was the most frequently cited scholar. The research hotspots have gradually shifted from cognitive function and outcome measurement to the development of new therapy models.

This study comprehensively examined the research hotspots and knowledge atlas of radiotherapy-related cognitive decline from a bibliometric perspective. Our results would assist scholars in identifying potential collaborators and significant literature in this field while also providing valuable guidance for future research directions.