Tackling global health security by building an academic community for One Health action.

BACKGROUND: One Health approach is crucial to tackling complex global public health threats at the interface of humans, animals, and the environment. As outlined in the One Health Joint Plan of Action, the international One Health community includes stakeholders from different sectors. Supported by the Bill & Melinda Gates Foundation, an academic community for One Health action has been proposed with the aim of promoting the understanding and real-world implementation of One Health approach and contribution towards the Sustainable Development Goals for a healthy planet. MAIN TEXT: The proposed academic community would contribute to generating high-quality scientific evidence, distilling local experiences as well as fostering an interconnected One Health culture and mindset, among various stakeholders on different levels and in all sectors. The major scope of the community covers One Health governance, zoonotic diseases, food security, antimicrobial resistance, and climate change along with the research agenda to be developed. The academic community will be supported by two committees, including a strategic consultancy committee and a scientific steering committee, composed of influential scientists selected from the One Health information database. A workplan containing activities under six objectives is proposed to provide research support, strengthen local capacity, and enhance global participation. CONCLUSIONS: The proposed academic community for One Health action is a crucial step towards enhancing communication, coordination, collaboration, and capacity building for the implementation of One Health. By bringing eminent global experts together, the academic community possesses the potential to generate scientific evidence and provide advice to local governments and international organizations, enabling the pursuit of common goals, collaborative policies, and solutions to misaligned interests.

Population Pharmacokinetics and Pharmacodynamics of Isoniazid and its Metabolite Acetylisoniazid in Chinese Population.

Objective: We aimed to establish a population pharmacokinetic (PPK) model for isoniazid (INH) and its major metabolite Acetylisoniazid (AcINH) in healthy Chinese participants and tuberculosis patients and assess the role of the NAT2 genotype on the transformation of INH to AcINH. We also sought to estimate the INH exposure that would achieve a 90% effective concentration (EC90) efficiency for patients with various NAT2 genotypes. Method: A total of 45 healthy participants and 157 tuberculosis patients were recruited. For healthy subjects, blood samples were collected 0-14 h after administration of 300 mg or 320 mg of the oral dose of INH; for tuberculosis patients who received at least seven days therapy with INH, blood samples were collected two and/or six hours after administration. The plasma concentration of INH and AcINH was determined by the reverse-phase HPLC method. NAT2 genotypes were determined by allele-specific amplification. The integrated PPK model of INH and AcINH was established through nonlinear mixed-effect modeling (NONMEM). The effect of NAT2 genotype and other covariates on INH and AcINH disposition was evaluated. Monte Carlo simulation was performed for estimating EC90 of INH in patients with various NAT2 genotypes. Results: The estimated absorption rate constant (Ka), oral clearance (CL/F), and apparent volume of distribution (V2/F) for INH were 3.94 ± 0.44 h-1, 18.2 ± 2.45 L⋅h-1, and 56.8 ± 5.53 L, respectively. The constant of clearance (K30) and the volume of distribution (V3/F) of AcINH were 0.33 ± 0.11 h-1 and 25.7 ± 1.30 L, respectively. The fraction of AcINH formation (FM) was 0.81 ± 0.076. NAT2 genotypes had different effects on the CL/F and FM. In subjects with only one copy of NAT2 *5, *6, and *7 alleles, the CL/F values were approximately 46.3%, 54.9%, and 74.8% of *4/*4 subjects, respectively. The FM values were approximately 48.7%, 63.8%, and 86.9% of *4/*4 subjects, respectively. The probability of target attainment of INH EC90 in patients with various NAT2 genotypes was different. Conclusion: The integrated parent-metabolite PPK model accurately characterized the disposition of INH and AcINH in the Chinese population sampled, which may be useful in the individualized therapy of INH.

The pharmacokinetics of tacrolimus in peripheral blood mononuclear cells and limited sampling strategy for estimation of exposure in renal transplant recipients.

PURPOSE: Intracellular exposure of tacrolimus (TAC) may be a better marker of therapeutic effect than whole blood exposure. We aimed to evaluate the influence of genetic polymorphism on the pharmacokinetics of TAC in peripheral blood mononuclear cells (PBMCs) and develop limited sampling strategy (LSS) models to estimate the area under the curve (AUC0-12h) in the PBMC of Chinese renal transplant patients. METHODS: Ten blood samples of each of the 23 renal transplant patients were collected 0-12h after 14 (10-18) days of TAC administration. PBMCs were separated and quantified. The TAC level in PBMCs was determined, and pharmacokinetic parameters were estimated by noncompartmental study. The AUC0-12h of TAC in whole blood was estimated by Bayesian approach based on a population pharmacokinetic model established in 65 renal transplant patients. The influence of CYP3A5 and ABCB1 genotypes on exposure was estimated. By applying multiple stepwise linear regression analysis, LSS equations for TAC AUC0-12h in the PMBC of renal transplant patients were established, and the bias and precision of various equations were identified and compared. RESULTS: We found a modest correlation between TAC exposure in whole blood and PBMC (r2 = 0.5260). Patients with the CYP3A5 6986GG genotype had a higher AUC0-12h in PBMCs than those with the 6986 AA or GA genotype (P = 0.026). Conversely, patients with the ABCB1 3435TT genotype had a higher AUC0-12h in PBMC than those with the 3435 CC and CT genotypes (P = 0.046). LSS models with 1-4 blood time points were established (r2 = 0.570-0.989). The best model for predicting TAC AUC0-12h was C2-C4-C6-C10 (r2 = 0.989). The model with C0.5-C6 (r2 = 0.849) can be used for outpatients who need monitoring to be performed in a short period. CONCLUSIONS: The CYP3A5 and ABCB1 genotypes impact TAC exposure in PBMCs, which may further alter the effects of TAC. The LSS model consisting of 2-4 time points is an effective approach for estimating full TAC AUC0-12h in Chinese renal transplant patients. This approach may provide convenience and the possibility for clinical monitoring of TAC intracellular exposure.

Population Pharmacokinetics and Bayesian Estimation of the Area Under the Concentration-Time Curve for Ganciclovir in Adult Chinese Renal Allograft Recipients After Valganciclovir Administration.

Valganciclovir (VGCV) is the prodrug of ganciclovir (GCV). The objective of this study was to establish a population pharmacokinetic model (PPK) of GCV to investigate the PK characteristics of GCV after administration of VGCV in adult Chinese renal allograft recipients. Seventy Chinese renal allograft recipients were given 450 mg (n = 41) or 900 mg (n = 29) VGCV daily. Blood samples were drawn 0-24 hours after 5 days' therapy, and GCV plasma levels were determined. The PPK model was constructed using nonlinear mixed-effects modeling, and the Bayesian estimation of AUC0-24h was constructed for an individual patient based on limited plasma samples. The PK of GCV was best described by a 2-compartment model with a first-order absorption process. The CL/F, V2 /F, Q/F, V3 /F, Ka , and lag time of GCV were 15.8 ± 0.71 L/h, 10.9 ± 2.38 L, 3.98 ± 0.40 L/h, 167 ± 44.0 L, 0.23 ± 0.0078 1/h, and 0.93 ± 0.017 hours, respectively. Clearance of creatinine was found to have a significant impact on the CL/F of GCV (P < .01). Sampling strategies consisted of plasma concentrations 0 and 2 and 0, 2, and 4 hours after VGCV administration were shown to be suitable for the estimation of the GCV AUC0-24h . The PPK model was acceptable and can describe the PK of GCV in Chinese renal transplant patients administered VGCV. The AUC0-24h of GCV in Chinese renal transplant patients can be calculated by a limited sampling strategy method.