Tag: Clinical trial

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<![CDATA[Open-label phase 2 trial tests IV Briumvi alongside antipsychotics for treatment-resistant schizophrenia, targeting B-cell depletion to improve symptoms and assess safety.]]>
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STAT+: Pharmalittle: We’re reading about a Novartis acquisition, Republicans backing clinical trial diversity, and more

Good morning, and welcome to a new week from STAT’s London outpost, with Andrew Joseph here filling in for Mr. Pharmalot. This country is celebrating its World Cup win last night (or rather, very early this morning local time — lots of bleary-eyed people out in the neighborhood today), and I can only hope that the U.S. will be in the same place tomorrow. Yet the World Cup (and Wimbledon) can’t completely distract from the news of the day, so onto the headlines we go. … 

Novartis is pushing deeper into antibody-drug conjugate development, paying $1.1 billion upfront to buy Myricx Bio for a pipeline based on a novel payload, Fierce Biotech writes. The Swiss pharma company has been slower to buy into ADCs than some of its peers, but it’s made its move with London-based Myricx, which is designing cancer treatments that deliver N-myristoyltransferase inhibitor (NMTi) payloads. It’s a bit of a different approach from other ADCs, which Novartis predicts could tackle resistance and other limitations of existing payloads, broadening the use of ADCs across multiple tumor types. 

While clinical trials got caught up in the Trump administration’s attack on policies related to diversity, equity, and inclusion, congressional Republicans would like to change that, STAT says. Last month, the Republican-controlled House passed a bill, mostly along party lines, to fund the Food and Drug Administration that was accompanied by a report that, while not legally binding, tells agency officials what congressional appropriators expected of them. The report states that it wants the FDA to continue implementing a law that requires companies to give the FDA their plans for diversifying clinical trials.

Continue to STAT+ to read the full story…

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STAT+: GOP lawmakers push Trump’s FDA to make sure clinical trials are diverse

WASHINGTON — Clinical trial policy got caught up in the Trump administration’s attack on policies related to diversity, equity, and inclusion. Republicans in Congress would like to change that. 

Days after Trump took office, the Health and Human Services Department began purging all references to DEI from the websites of its agencies. Those efforts were supposed to target DEI initiatives focused on hiring practices, communications, and social issues.

But supporters of clinical trial diversity say the policy has nothing to do with DEI in that sense. Instead, it aims to ensure that clinical trials enroll people who are similar to the patients who would use the drugs and medical devices being tested. 

Continue to STAT+ to read the full story…

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Agreement Between Reasoning-Oriented Generative AI Models and Clinical Educators in Evaluating Japanese Objective Structured Clinical Examination Transcripts: Preliminary Comparative Study

Background: Medical interview training faces limitations in both implementation and evaluation. While generative artificial intelligence (GenAI) offers a potential solution, it remains unclear whether reasoning-oriented models improve evaluation, particularly for the Japanese language. Objective: We assessed scoring patterns to evaluate the agreement between reasoning-oriented GenAI model scores and clinical educator consensus ratings in Japanese medical interview training. Methods: This study was conducted at a medical university in Japan using original Japanese-language text data derived from medical interview training. Postgraduate year 1 and 2 residents were involved. Two blinded human clinical educators independently evaluated the transcripts and reached consensus through discussion. These consensus ratings were used as a practical reference standard, while preconsensus agreement was also assessed to characterize interhuman variability. Two GenAI models, GPT-5.2 Thinking (OpenAI) and Gemini 3.0 Pro (Google LLC), independently evaluated the same transcripts directly. Each GenAI model generated a single zero-shot evaluation per transcript using default settings. All evaluations used a standardized 6-domain Objective Structured Clinical Examination rubric (patient care, history taking, physical examination, accuracy and organization of clinical information, clinical reasoning, and management) scored on a 1‐6 Likert scale, where 1 indicates inferior, and 6 indicates excellent. We compared mean evaluation scores using the Wilcoxon signed-rank test and assessed interrater reliability using intraclass correlation coefficients between the GenAI models and the clinical educators. Results: Clinical educators and both GenAI models rated the entire dataset of 40 transcripts by 20 included residents. Clinical educator consensus ratings yielded the highest overall mean scores (5.18, 95% CI 5.06 to 5.30). Comparatively, both GenAI models demonstrated significantly lower scores: GPT-5.2 Thinking assigned the lowest overall score (3.68, 95% CI 3.62 to 3.72; <.001), followed by Gemini 3.0 Pro (4.09, 95% CI 3.97 to 4.21; <.001). This discrepancy was most pronounced in the management domain, where GPT-5.2 Thinking assigned 2.93 (95% CI 2.79 to 3.06) compared with the clinical educator consensus mean score of 5.20 (95% CI 4.91 to 5.49). Agreement between the GenAI models and the clinical educator consensus ratings was poor across all domains, with overall intraclass correlation coefficients of 0.04 (95% CI 0.00 to 0.09) for GPT-5.2 Thinking and 0.22 (95% CI 0.10 to 0.35) for Gemini 3.0 Pro. Conclusions: In this preliminary, single-center, transcript-based Japanese-language study, single-run zero-shot evaluations by GPT-5.2 Thinking and Gemini 3.0 Pro showed lower scores and poor agreement with the clinical educator consensus ratings. These findings should be interpreted cautiously because multiple outputs, prompt-sensitivity analyses, local validation, and model-parameter comparisons were not performed. Under the specific conditions tested, these models should not be used as standalone evaluators for Japanese Objective Structured Clinical Examination medical interview transcripts. Whether these models can provide useful formative feedback remains a hypothesis. Trial Registration: UMIN-CTR Clinical Trial UMIN000053747; https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000061336
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Polypill for heart failure with reduced ejection fraction: the POLY-HF randomized trial

Nature Medicine, Published online: 02 July 2026; doi:10.1038/s41591-026-04504-5

In an open-label randomized trial, a polypill containing three types of heart failure medication (metoprolol, spironolactone and empagliflozin) improved left ventricular ejection fraction and resulted in a smaller number of heart failure hospitalizations or emergency room visits at 6 months, as compared to enhanced usual care.

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Impact of an mHealth App on Digital Transformation: Randomized Clinical Trial on Strengthening Digital Skills in Older Women

Background: The rapid growth of digital technologies has transformed daily activities, health management, and social interaction. Older adults, however, continue to face challenges in adopting and using these tools due to limited previous exposure, age-related sensory or cognitive decline, and low digital confidence. In Brazil, internet access among adults aged 60 years or older has increased, yet digital exclusion persists, worsening health disparities. Mobile health (mHealth) apps offer a potential strategy to promote digital inclusion, strengthen digital competencies, and support healthy aging. Nonetheless, studies show that culturally adapted, multidisciplinary interventions for this group remain scarce and are rarely assessed through both quantitative and qualitative methods. Objective: This study aimed to evaluate the impact of a lifestyle mHealth app on improving digital skills, as well as to analyze the level of satisfaction and usability of the app. Methods: In this mixed methods study, a 14-week randomized clinical trial was conducted in Ribeirão Preto, São Paulo, Brazil. A total of 40 older adult women were randomized into an intervention group (n=21), who used the mobile app, and a control group (n=19). Digital competencies were measured before and after the intervention using a semistructured questionnaire based on the (MCDMSênior; Digital Competency Model for M-learning with a focus on older adults) framework, covering 6 domains—basic technology use, internet navigation, mobile app use, online research, digital communication, and usage of digital resources. Additionally, satisfaction with the educational content was evaluated using the suitability assessment of materials, and system usability was assessed using the System Usability Scale. Qualitative data were collected through semistructured, in-person interviews conducted immediately after the intervention with all intervention participants. Interviews explored perceptions of the app’s usability, satisfaction with its content, barriers, and facilitators to engagement, and perceived changes in digital skills. All interviews were audio-recorded, transcribed, and analyzed thematically by 2 independent researchers using an inductive coding approach. Results: Postintervention analyses revealed significant differences in specific digital competencies. The intervention group demonstrated a moderate improvement in internet navigation skills, while gains in basic technology use and digital communication were minimal. Conversely, the control group exhibited moderate improvement in basic technology skills and lower effects in online research and digital communication. Overall, satisfaction with the educational content was low, and usability was rated as average. Qualitative findings indicated that, although participants valued the clarity of navigation and cultural relevance, persistent age-related fears and insecurities in using digital technologies were reported. Participants highlighted the need for more personalized guidance, ongoing motivational support, and technical adjustments to improve usability and engagement. Conclusions: mHealth apps can effectively enhance certain digital competencies in older women, particularly internet navigation, but improvements in content suitability and usability are needed. Refinements in design and tailored support are essential to overcome age-related barriers and foster digital inclusion. Trial Registration: Brazilian Registry of Clinical Trials RBR-6wgkzs8; https://ensaiosclinicos.gov.br/rg/RBR-6wgkzs8
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<![CDATA[Track latest neuropsychiatry breakthroughs: phase 3 narcolepsy study launches, new depression and PTSD therapies advance, and FDA approvals reshape care.]]>