Almost half of individuals with hypertension fail to achieve recommended blood pressure (BP) goals. Pharmacogenetic gene-drug interactions may alter the efficacy of antihypertensive agents. We conducted a multicenter randomized controlled sub-study of participants (N = 1874) with hypertension and self-reported African ancestry to determine whether pharmacogenetic return of results (RoR) would improve systolic blood pressure (SBP) at 3 months. Participants were randomized to immediate pharmacogenetic RoR (intervention) or delayed RoR at trial completion (control). Clinical decision support conveyed recommendations for YEATS4-guided thiazide diuretic selection and NAT2-guided hydralazine dosing. Prespecified subgroup analyses included those with uncontrolled BP (baseline SBP >= 140 or DBP >= 90 mm Hg) and actionable genotypes. Immediate RoR did not improve SBP at 3 months in a broad population of hypertensive adults with controlled and uncontrolled SBP (covariate-adjusted change in SBP between groups: -0.3 +/- 0.74 mm Hg, 95% CI: -1.8, 1.2). In participants with an actionable YEATS4 genotype (N = 867) predicting reduced thiazide efficacy, immediate RoR led to greater SBP reduction at 3 months (-2.46 mm Hg, 95% CI: -4.57 to -0.36). In participants with uncontrolled hypertension at baseline (N = 659), immediate RoR led to a greater reduction in SBP (-2.9 +/- 0.74 mm Hg, 95% CI: -5.6, -0.3). Although no SBP reduction was observed in the whole cohort, participants with an actionable YEATS4 genotype or uncontrolled BP who received immediate RoR had a significantly greater SBP improvement than those with delayed RoR. Future studies of antihypertensive pharmacogenetics should recruit individuals with uncontrolled BP and actionable genotypes.
Concomitant congestive heart failure (CHF) and diabetes mellitus (DM) patients frequently are treated with polypharmacy, thus potentially increasing the risk of drug-drug interactions (pDDIs). Conventional DDI screening methods often fail to distinguish clinically significant interactions from recommended therapeutic combinations. This study assessed the prevalence, severity, and clinical consequences of pDDIs in hospitalized patients with CHF and DM. This ambispective, cross-sectional study included 144 hospitalized patients with CHF and DM. We used the Micromedex and Lexicomp databases to check prescriptions. We classified clinically relevant DDIs and therapeutic combinations requiring routine monitoring by severity. 207 pDDIs were identified, of which 84.1% were moderate and 15.9% severe. Polypharmacy was a major risk factor for the DDI burden, and over seven drugs were associated with significantly more interactions than fewer drugs (P < 0.001). Polypharmacy was an independent predictor of clinically significant DDI (AOR 3.42; 95% CI 1.78-6.59) in the multivariate analysis. The most commonly seen combinations (statin-ezetimibe and sulfonylurea-metformin therapy) are guideline-recommended and do not need to be avoided. Clinical pharmacists and prescribing clinicians performing context-aware interpretation of DDI alerts by differentiating between guideline-recommended therapeutic combinations requiring monitoring and truly actionable interactions can reduce alert fatigue, preserve evidence-based therapy, and support safe prescribing in complex CHF-DM patients.
Unconjugated antisense oligonucleotides (ASOs) and GalNAc-conjugated small interfering RNAs (siRNAs) have emerged as transformative therapeutic modalities, but their translation remains hindered by complex pharmacokinetics characterized by rapid plasma clearance, heterogeneous tissue uptake, and prolonged intracellular retention. Physiologically based pharmacokinetic (PBPK) modeling offers a mechanistic framework to integrate these processes across species, yet applications to oligonucleotides remain limited, and existing efforts are typically restricted to specific chemistries or routes of administration. This study aimed to develop a cross-species PBPK platform to characterize the plasma and tissue disposition of unconjugated ASOs and GalNAc-siRNAs in preclinical species and humans, and to evaluate the consistency of estimated drug-specific parameters with pre-specified allometric scaling relationships within the domain of compounds and routes considered. Published datasets spanning mice, rats, non-human primates, and humans were integrated for representative unconjugated ASOs (Malat-1, GluR1, p-tau, tominersen) and GalNAc-siRNAs (ALN-AT3, givosiran, fitusiran). The PBPK model incorporated 11 tissue compartments, cerebrospinal fluid substructures, tissue substructures, endosomal trafficking, non-specific binding in kidney and liver, and ASGPR-mediated internalization for GalNAc-siRNAs. Parameters for endocytosis, exocytosis, and degradation were estimated, and estimated values were compared with pre-specified allometric exponents to assess physiological plausibility (i.e., as a consistency check rather than independent inference of scaling laws). The model captured plasma, liver, kidney, and CNS profiles across species, reproducing rapid systemic clearance with prolonged tissue half-lives. Estimated parameter values for endocytosis, exocytosis, and non-specific kidney binding were consistent with pre-specified allometric exponents (b = -0.25 and -0.2, respectively), supporting the physiological plausibility of the estimates. Sensitivity analyses identified endocytosis and rate of degradation as dominant determinants of systemic and tissue disposition. This work establishes a translational PBPK platform for unconjugated ASOs and GalNAc-conjugated siRNAs, enabling quantitative interspecies extrapolation within the domain of the compounds, routes, and species studied. The framework provides a mechanistic basis to support dose selection, safety assessment, and clinical translation for these subclasses; extrapolation to other oligonucleotide subclasses (e.g., GalNAc-ASOs, unconjugated siRNAs, LNP-formulated oligonucleotides) will require additional datasets and dedicated validation.
