赛诺菲制药公司

Contact mechanics models are reviewed for estimating as-received and dry-coated fine powder adhesion, required for computing granular Bond number (Bog). Van der Waals-dominated adhesion models are examined, starting with smooth particle approximation, uncovering particle size and surface energy as key factors, to singleasperity models establishing the mechanistic basis for nano-sized guest particle selection, to multi-asperity Chen model, uncovering the importance of guest surface area coverage (SAC) and deterministic contact regime transitions; host-host, host-guest, and guest-guest. For smooth particles, the models predict over two orders of magnitude adhesion reduction after dry coating. However, for rough particles, the extent of reduction without dry coating and the roughness scale assumptions, e.g., 200nm, or a power-law function of the host size, require closer examination. Contact force analysis identifies similar to 100 nm as a conservative critical roughness beyond which adhesion is dominated by asperity-asperity contacts rather than particle-particle interactions. That explains lower cohesion as well as lesser adhesion reduction after dry coating of macro-rough particles compared to smoother counterparts, implying smooth surface Bog as overestimated. Specific surface area deviation between BET and PSD-derived values is identified as a practical diagnostic for such cases. The monolayer guest distribution assumption is shown as invalid at insufficient processing intensity due to guest agglomeration; a fractalporosity framework is developed here to quantify the reduction in SAC and enlargement of effective guest size. The framework is assessed against flowability data for 27 powders, and against ten batches of a rod-like industrial API. Overall, a quantitative foundation toward a predictive science of dry particle coating is presented by connecting contact models to Bog estimation, helping identify where assumptions require further scrutiny.

Despite receiving triple therapy (i.e., long-acting β2-agonist + long-acting muscarinic antagonist + inhaled corticosteroid), patients with chronic obstructive pulmonary disease (COPD) continue to experience exacerbations. This study aimed to investigate the moderate and severe annualized exacerbation rate (AER) and healthcare resource utilization of patients with COPD on triple therapy in China, addressing a significant evidence gap regarding the clinical and economic disease burden in this population. This retrospective cohort study was conducted using the Chongqing Regional Electronic Health Record Database (2018–2022). Patients with COPD aged ≥ 40 years who had received ≥ 3 months of triple therapy during the 12-month baseline period were included. AER, COPD-related hospital visits, length of hospital stay and readmissions, and direct medical costs during the 12-month observation period were analyzed. A total of 6393 patients with COPD on triple therapy were included in the study. Among patients with available data, 17.3

Obese patients hospitalized for surgery are at high risk of venous thromboembolism (VTE). The optimal dose and duration of thromboprophylaxis with low molecular weight heparin for these patients are uncertain. To assess the time-course, rates and risk factors for VTE and major bleeding (MB) in a population of surgical patients with obesity receiving pharmacological thromboprophylaxis with enoxaparin. Patients with body mass index (BMI) > 30 kg/m2 hospitalized with surgeries between 2010 and 2021 who received thromboprophylaxis with enoxaparin were selected from the US Optum database. Exclusion criteria were VTE, MB, or surgery in previous 90-days, and ongoing anticoagulant treatment or dual antiplatelet therapy. VTE and MB event rates over a 90-day follow-up post enoxaparin initiation were estimated via the Kaplan-Meier (KM) method. Risk factors associated with outcome events were identified via Cox proportional hazard models. A total of 30,492 patients met selection criteria, 12,058 patients received the standard dose, with 18,300 receiving higher doses. KM event rates at 90-days for VTE and MB were 2.5

The impending patent cliff projected between 2028–2030 poses significant commercial and strategic challenges for innovative pharmaceutical and biotechnology companies. To sustain growth and maintain competitive positioning, organizations are increasingly relying on strategic mergers, acquisitions, and partnerships to replenish pipelines. However, systematic quantitative strategies and framework for asset evaluation remain limited. This review outlines how clinical pharmacology and pharmacometrics (CPP) can support asset evaluation and decision-making during the asset due diligence. First, CPP spans the entire drug development continuum, providing a quantitative framework for evaluating external assets, including pharmacological plausibility, dosing feasibility, and overall development risks. Second, Model-informed drug development (MIDD) approaches can be applied to predict human pharmacokinetics, inform dose selection, and estimate the probability of technical and regulatory success. Third, we examine the emerging role of artificial intelligence and machine learning in asset evaluation and portfolio decision-making, by discovering prognostic and predictive factors, and identifying the patient sub-group. We also introduce NewCo as an emerging drug-development and business model, where quantitative strategies may be deployed. Further, we address cognitive biases, such as confirmation bias and sunk cost fallacies that can influence acquisition outcomes. Importantly, we propose the development of a bias-aware, fit-for-purpose corporate template to integrate CPP and MIDD insights, standardize evaluation criteria, and support cross-functional decision-making during asset due diligence. Embedding quantitative and bias-mitigated CPP frameworks into due diligence workflows, can help identify high-value opportunities, de-risk development uncertainties, and accelerate delivery of innovative therapies to patients with unmet medical needs.

Although effective pertussis vaccines are available and have been incorporated into national immunization programs for infants and children, and adolescents and adults in some countries, pertussis remains endemic worldwide. Periodic outbreaks occur every 2 to 5 years. In 2013, France revised its pediatric vaccination program, transitioning from a 3 + 1 to a 2 + 1 schedule. The effects of this change have raised some concerns; however, data on the effectiveness of pediatric vaccines in France post 2013 remain limited. This matched case-control study aimed to estimate the effectiveness of vaccination against pertussis in children born in France between 2013 and 2019, using the French National Health Data System. Children were included in the study if they were alive and free of pertussis at 6 weeks of age, and if their mother-child linkage was available. Pertussis-related hospitalizations were captured using the International Classification of Diseases-10 codes (A37.0 and A37.9), and vaccine exposure status was confirmed using ATCC codes (J07CA02, J07CA06, and J07CA09). The odds ratio (OR) of exposure to vaccine against pertussis for 1, 2, and 3 effective doses was calculated using conditional logistic regression models. Vaccine effectiveness (VE) was estimated as (1-adjusted OR) × 100% in at-term infants. In total, 1,481,884 children were included in the study. When stratified by age groups, a gradient of increasing VE was observed, with highest VE (93.4%) observed among children aged 11.5 to 60 months who were fully vaccinated according to 2 + 1 schedule and lowest (24.1%) among children aged 2 to 4.5 months who received only the first dose. In sensitivity analyses, imputation of missing data on vaccinations potentially received outside the healthcare insurance setting (Protection maternelle et infantile) resulted in an approximately 6% increase in VE. Results demonstrated that adherence to the 2 + 1 schedule provided effective protection against pertussis in full term children in France.