The early market access vehicle - An innovative demand-driven model to catalyse introduction of new optimal health products in low- and middle-income countries.

Low-and middle-income countries (LMICs) account for a significant proportion of the burden of disease for communicable illnesses globally; with malaria, tuberculosis (TB), and HIV/AIDS being the leading causes of death. Despite this disparity, LMICs often have limited or delayed access to newer optimal health products compared to high-income countries (HICs). This limitation in access, driven by a myriad of barriers, undermines the potential health benefits that could be gained in LMICs through the introduction of better health products.

Implementation of the advanced HIV disease package of care using a public health approach: lessons from Nigeria.

Background: Nigeria adapted the WHO package of care for Advanced HIV Disease (AHD) in 2020. The package includes CD4 + cell count testing to identify People Living with HIV (PLHIV) with AHD, screening and treatment of opportunistic infections, rapid antiretrovirals (ART) initiation, and intensive adherence follow-up. The national program adopted a phased approach in the rollout of the AHD package of care to learn lessons from a few representative health facilities before scaling up across the country.

Case report: Single gene testing and comprehensive genomic profiling in non-small cell lung cancer-a case series of divergent results from a large reference laboratory.

Clinical management of non-small cell lung cancer (NSCLC) requires accurate identification of tumor-specific genetic alterations to inform treatment options. Historically, providers have relied on single-gene testing (SGT) for actionable variants due to a perception of cost-effectiveness and/or efficient turnaround time compared to next-generation sequencing (NGS). However, not all actionable variants may be evaluated through SGT modalities, and an SGT approach can exhaust valuable tissue needed for more comprehensive analyses.

A consensus-based classification workflow to determine genetically inferred ancestry from comprehensive genomic profiling of patients with solid tumors.

Disparities in cancer diagnosis, treatment, and outcomes based on self-identified race and ethnicity (SIRE) are well documented, yet these variables have historically been excluded from clinical research. Without SIRE, genetic ancestry can be inferred using single-nucleotide polymorphisms (SNPs) detected from tumor DNA using comprehensive genomic profiling (CGP). However, factors inherent to CGP of tumor DNA increase the difficulty of identifying ancestry-informative SNPs, and current workflows for inferring genetic ancestry from CGP need improvements in key areas of the ancestry inference process.