Inspirion Delivery Technologies · therapeutic agent
abuse-deterrent extended release tablet technology is a therapeutic agent developed by Inspirion Delivery Technologies. It is approved for therapeutic indications via others.
| Company | Inspirion Delivery Technologies |
| Route | Others |
| Status | Approved |
abuse-deterrent extended release tablet technology is developed for 1 unique indication across 1 therapeutic area.
| Therapeutic Area | Condition | Phase |
|---|---|---|
| Surgical and medical procedures | Oral appliance application | ✓ Approved |
Behzadifar Masoud M
Qin Ying Y, Zhou Rushuang R, Ming Yali Y, Li Bohao B et al.
Navigating a vast formulation-preparation design space that is highly sensitive to perturbations makes trial-and-error approaches inefficient and costly for diverse clinical needs. Here, we introduce an expert-mimic AI framework called E-MAF that integrates a process-aware surrogate with an optimized genetic algorithm to emulate coarse-to-fine reasoning, autonomously generating lab-ready designs tailored to desired release profiles. We show that E-MAF delivers on-demand release and shortens design cycles from 6-12 months to approximately 1 hour. We demonstrate that in vitro release, in vivo pharmacokinetics and therapeutic effects match or surpass commercial benchmarks across 7 active pharmaceutical ingredients. We show that E-MAF also enables release profiles that are hard to achieve by conventional approaches, exemplified by ≤2% risperidone burst within 1 h and near-zero-order release over ~28 days in vivo. These results demonstrate E-MAF's potential to accelerate polymeric controlled-release system development and drug-delivery industrialization.
Courties Alice A, Winkler Tobias T, Conaghan Philip G PG, Berenbaum Francis F
Knee osteoarthritis (OA) is the most prevalent form of OA and a leading cause of chronic pain and disability worldwide. Its growing burden, driven mainly by ageing and obesity, is associated with major societal costs and increased cardiovascular mortality. Knee OA is now recognized as a heterogeneous whole-joint disease involving biomechanical, metabolic, inflammatory, osteochondral and neurovascular mechanisms. This complexity helps to explain why existing analgesics have modest efficacy and why disease-modifying OA drug development has repeatedly faltered. The therapeutic landscape is nevertheless evolving rapidly. Emerging symptomatic strategies include incretin-based therapies (semaglutide is the first to show substantial benefits for pain and function), neurotrophin modulation, extended-release intra-articular glucocorticoids, lubricating injectables and image-guided neurovascular interventions. In parallel, candidate disease-modifying OA drugs target cartilage anabolism, Wnt signalling, matrix-degrading enzymes, subchondral bone remodelling, immunometabolic pathways and local gene therapy. Several treatments, including locally administered GLP1 receptor agonists, the anabolic agent TPX-100 and intra-articular IL-1 receptor antagonist gene therapy, have shown encouraging signals, whereas mesenchymal stromal cell therapies have thus far demonstrated inconsistent efficacy across phase III clinical trials, highlighting the need for further standardization of mesenchymal stromal cell products and optimization of patient selection. Recent advances signal a shift towards a more diverse therapeutic landscape for knee OA, with emerging opportunities to target both symptoms and the underlying mechanisms of disease.
Ali Muhammad Abdullah MA, Nawaz Adil A, Sethi Furqan Ahmad FA, Alam Umama U et al.
The optimal duration of dual antiplatelet therapy (DAPT) following drug-eluting stent implantation remains uncertain. We evaluated extended DAPT versus aspirin monotherapy in patients who completed approximately 12 months of uneventful DAPT after percutaneous coronary intervention. PubMed, Embase, and Web of Science were searched through August 2026 for randomized controlled trials comparing these strategies. The primary outcome was myocardial infarction (MI); secondary outcomes included all-cause mortality, cardiac death, stent thrombosis, repeat revascularization, stroke, and clinically relevant bleeding (Bleeding Academic Research Consortium type 2-5). Risk ratios (RRs) with 95% confidence intervals (CIs) were pooled using a Mantel-Haenszel random-effects model. Certainty was assessed using Grading of Recommendations Assessment, Development and Evaluation (GRADE), and trial sequential analysis was performed for MI. Six trials involving 28,601 patients were included. Extended DAPT significantly reduced MI compared with aspirin monotherapy (RR, 0.66; 95% CI, 0.51-0.85; P = 0.001; I2 = 37%). No significant differences were observed in all-cause mortality, cardiac death, stent thrombosis, repeat revascularization, or stroke. Clinically relevant bleeding was also not significantly different (RR, 1.19; 95% CI, 0.66-2.15; P = 0.56), although substantial heterogeneity was observed (I2 = 87%) and certainty was low. GRADE certainty was high for MI, cardiac death, and repeat revascularization; moderate for all-cause mortality; and low for stent thrombosis and bleeding. Trial sequential analysis for MI crossed the conventional significance boundary but not the trial sequential monitoring boundary or required information size. Extended DAPT may reduce MI, but individualized assessment of ischemic and bleeding risk remains important, and further adequately powered trials are warranted.
Sitsky Sarina S, Crowther Rian H RH, Kelly Vincent G VG, Wilkins Luke L et al.
Virtual technology offers a promising tool for encouraging engagement in exercise, as it can provide the user with enhanced visual stimuli and accessible metrics; however, the specific features within that technology that contribute to motivation and participation require further investigation. This study examined how different visual displays and the presence of a second rider influenced motivation to exercise using virtual technology. Twenty-four young adults completed a 3-km cycling course on the same virtual track under three counterbalanced conditions including (a) a metrics-only ride, where a screen in front of the rider displayed only standard performance variables (e.g., power, cadence), (b) a solo-virtual ride, which was identical to the previous condition, but with the addition of the participant being depicted on the screen as an avatar amongst virtual scenery, and (c) a paired-virtual ride, that contained the same elements as the previous two conditions, but with the addition of a second rider represented on the screen as an avatar. The quantitative results, which included performance-related variables (cadence, power, speed, and heart rate), measures of intrinsic motivation, and ratings of perceived exertion, revealed significantly higher values for the paired-virtual condition compared to both the metrics-only and the solo-virtual conditions. Differences between the metrics-only and the solo-virtual conditions were isolated to interest-enjoyment and effort-importance. Brief interviews with participants indicated that the paired-virtual condition produced heightened levels of enjoyment and competitive drive which motivated participants to exert more effort. The solo-virtual condition was reported to be relaxing, but it was also reported as the least engaging. The metrics-only condition provoked negative emotions due to the absence of distractions and a heightened focus on internal cues. The results highlight the psychological mechanisms that influence motivation and engagement when using virtual exercise technology.
Lin Qin Q, Fu Mengxue M, Chen Pei P, Zhao Jiaorong J et al.
Generative AI has reshaped healthcare, yet multimorbid older adults face digital divide barriers limiting its safe application. Existing qualitative evidence on their AI-assisted complex health decision-making remains scarce, lacking integrated theoretical interpretation. Guided by an integrated framework combining the Technology Acceptance Model, Senior Technology Acceptance Model and Burden of Treatment Theory, this study explored older adults' perceived usefulness and ease of generative AI for health decisions, mobilizable personal-social resources, and how technology perceptions shape dynamic usage behaviors and decision quality. From September to December 2025, 16 multimorbid seniors were recruited via purposive maximum variation sampling from an urban community health center in eastern China. Face-to-face semi-structured interviews were conducted, with reflexive thematic analysis following COREQ guidelines. Based on interviews with 16 participants, four themes were identified: (1) Perceived usefulness, which was mainly reflected in four dimensions: initial situational triggers prompting AI consultation, convenient access to information, integrated support for multimorbidity management, and enhanced decision-making confidence. (2) Perceived ease of use: Participants' perceptions of the ease of use of generative AI showed significant individual differences and context dependence. (3) Resource mobilization: Successful use of generative AI rarely depended on independent individual effort but required the mobilization of diverse personal resources and social support. (4) Behavioral intention and actual use: The generative AI usage behavior of older adults with multimorbidity exhibited dynamic evolutionary characteristics; its trajectory was not linear acceptance and continuous use, but a complex process involving attempts, interruptions, resumption, or permanent abandonment. This study reveals that AI use among older adults with multimorbidity is not merely a technology adoption behavior, but an adaptive strategic choice made under the pressure of managing multiple chronic conditions. Only by fully considering the special needs of patients with multimorbidity in technology design and service provision can the safe and effective application of generative AI in elderly chronic disease management be truly realized. Not applicable. This study did not involve clinical trials.
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