Emerging Therapeutics, Technologies, and Drug Development Strategies to Address Patient Nonadherence and Improve Tuberculosis Treatment.

Imperfect medication adherence remains the biggest predictor of treatment failure for patients with tuberculosis. Missed doses during treatment lead to relapse, tuberculosis resistance, and further spread of disease. Understanding individual patient phenotypes, population pharmacokinetics, resistance development, drug distribution to tuberculosis lesions, and pharmacodynamics at the site of infection is necessary to fully measure the impact of adherence on patient outcomes.

Population Pharmacokinetic Method to Predict Within-Subject Variability Using Single-Period Clinical Data.

Sample sizes for single-period clinical trials, including pharmacokinetic studies, are statistically determined by within-subject variability (WSV). However, it is difficult to determine WSV without replicate-designed clinical trial data, and statisticians typically estimate optimal sample sizes using total variability, not WSV. We have developed an efficient population-based method to predict WSV accurately with single-period clinical trial data and demonstrate method performance with eperisone.

Modeling the potential impact of emerging innovations on achievement of Sustainable Development Goals related to maternal, newborn, and child health.

Background: Innovations that improve the affordability, accessibility, or effectiveness of health care played a major role in the Millennium Development Goal achievements and will be critical for reaching the ambitious new Sustainable Development Goal (SDG) health targets. Mechanisms to identify and prioritize innovations are essential to inform future investment decisions.

Methods: Innovation Countdown 2030 crowdsourced health innovations from around the world and engaged recognized experts to systematically assess their lifesaving potential by 2030.

Modeling the public health impact of malaria vaccines for developers and policymakers.

Background: Efforts to develop malaria vaccines show promise. Mathematical model-based estimates of the potential demand, public health impact, and cost and financing requirements can be used to inform investment and adoption decisions by vaccine developers and policymakers on the use of malaria vaccines as complements to existing interventions. However, the complexity of such models may make their outputs inaccessible to non-modeling specialists.

The MANDATE model for evaluating interventions to reduce postpartum hemorrhage.

Objective: To create a comprehensive model of the comparative impact of various interventions on maternal, fetal, and neonatal (MFN) mortality.

Methods: The major conditions and sub-conditions contributing to MFN mortality in low-resource areas were identified, and the prevalence and case fatality rates documented. Available interventions were mapped to these conditions, and intervention coverage and efficacy were identified.