Disparities in receipt of medications for opioid use disorder among pregnant women.

Background: Medications for opioid use disorder (MOUD) improve outcomes for pregnant women and infants. Our primary aim was to examine disparities in maternal MOUD receipt by family sociodemographic characteristics. Methods: This retrospective cohort study included mother-infant dyads with Medicaid-covered deliveries in Tennessee from 2009 to 2016. First, we examined family sociodemographic characteristics - including race/ethnicity, rurality, mother's primary language and education level, and whether paternity was recorded in birth records - and newborn outcomes by type of maternal opioid use. Second, among pregnant women with OUD, we used logistic regression to measure disparities in receipt of MOUD by family sociodemographic characteristics including interactions between characteristics. Results: Our cohort from Medicaid-covered deliveries consisted of 314,965 mother-infant dyads, and 4.2 percent were exposed to opioids through maternal use. Among dyads with maternal OUD, MOUD receipt was associated with lower rates of preterm and very preterm birth. Logistic regression adjusted for family sociodemographic characteristics showed that pregnant women with OUD in rural versus urban areas (aOR: 0.66; 95% CI: 0.60-0.72) and who were aged ≥35 years versus ≤25 years (aOR: 0.75; 95% CI: 0.64-0.89) were less likely to have received MOUD. Families in which the mother's primary language was English (aOR: 2.47; 95% CI: 1.24-4.91) and paternity was recorded on the birth certificate (aOR: 1.30; 95% CI: 1.19-1.42) were more likely to have received MOUD. Regardless of high school degree attainment, non-Hispanic Black versus non-Hispanic White race was associated with lower likelihood of MOUD receipt. Hispanic race was associated with lower likelihood of MOUD receipt among women without a high school degree. Conclusions: Among a large cohort of pregnant women, we found disparities in receipt of MOUD among non-Hispanic Black, Hispanic, and rural pregnant women. As policymakers consider strategies to improve access to MOUD, they should consider targeted approaches to address these disparities.

Rapid generation of potent antibodies by autonomous hypermutation in yeast

The predominant approach for antibody generation remains animal immunization, which can yield exceptionally selective and potent antibody clones owing to the powerful evolutionary process of somatic hypermutation. However, animal immunization is inherently slow, has poor compatibility with certain antigens (e.g., integral membrane proteins), and suffers from self-tolerance and immunodominance, which limit the functional spectrum of antibodies that can be obtained. Here, we describe Autonomous Hypermutation yEast surfAce Display (AHEAD), a synthetic recombinant antibody generation technology that imitates somatic hypermutation inside engineered yeast. In AHEAD, antibody fragments are encoded on an error-prone orthogonal DNA replication system, resulting in Saccharomyces cerevisiae populations that continuously mutate surface-displayed antibody repertoires. Simple cycles of yeast culturing and enrichment for antigen binding drive the evolution of high-affinity antibody clones in a readily parallelizable process that takes as little as 2 weeks. We applied AHEAD to generate nanobodies against the SARS-CoV-2 S glycoprotein, a GPCR, and other targets. The SARS-CoV-2 nanobodies, concurrently evolved from an open-source naive nanobody library in 8 independent experiments, reached subnanomolar affinities through the sequential fixation of multiple mutations over 3-8 AHEAD cycles that saw [~]580-fold and [~]925-fold improvements in binding affinities and pseudovirus neutralization potencies, respectively. These experiments highlight the defining speed, parallelizability, and effectiveness of AHEAD and provide a template for streamlined antibody generation at large with salient utility in rapid response to current and future viral outbreaks.