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According to the World Health Organization, the number of tuberculosis (TB) infections and the drug-resistant burden worldwide increased by 4.5% and 3.0%, respectively, between 2020 and 2021. Disease severity and complexity drive the interest for undertaking new clinical trials to provide efficient treatment to limit spread and drug resistance. TB Alliance conducted a phase 2 study in 106 patients to guide linezolid (LZD) dose selection using early bactericidal activity over 14 days of treatment. LZD is highly efficient for drug-resistant TB treatment, but treatment monitoring is required since serious adverse events can occur. The objective of this study was to develop a pharmacokinetic-pharmacodynamic (PKPD) model to analyze the dose-response relationship between linezolid exposure and efficacy biomarkers. Using time to positivity (TTP) and colony-forming unit (CFU) count data, we developed a PKPD model in six dosing regimens, differing on LZD dosing intensity. A one-compartment model with five transit absorption compartments and non-linear auto-inhibition elimination described best LZD pharmacokinetic characteristics. TTP and CFU logarithmic scaled [log(CFU)] showed a bactericidal activity of LZD against Mycobacterium tuberculosis . TTP was defined by a model with two significant covariates: the presence of uni- and bilateral cavities decreased baseline TTP value by 24%, and an increase on every 500 mg/L/h of cumulative area under the curve increased the rate at which TTP and CFU change from baseline by 20% and 11%, respectively., Clinical Trials: This study is registered with ClinicalTrials.gov as NCT02279875., Competing Interests: The authors declare no conflict of interest.

Background: Daily dosing of tenofovir disoproxil fumarate, with or without emtricitabine, has high efficacy in preventing human immunodeficiency virus (HIV) infection when individuals are adherent. The target protective plasma concentration of tenofovir (TFV), however, is not fully understood. The aim of this study is to estimate the protective TFV plasma concentration., Methods: Participant data from TFV-based daily oral and topical active arms of phase 3 trials (iPrEx, VOICE, and Partners PrEP) were pooled (n = 2950). Individual specific risk scores (low and high risk) of acquiring HIV, based on an earlier placebo analysis, were created. Longitudinal TFV pharmacokinetics (PK), HIV outcome, individual risk scores and the effect of sex at birth data were integrated and analyzed using non-linear mixed effects models., Results: Around 50% of the individuals were estimated to be adherent, which differed from self-reported adherence (∼90%) and large variation between longitudinal adherence patterns were identified. Following oral administration, the estimated protective TFV trough concentration was substantially higher in high-risk females (45.8 ng/mL) compared with high-risk males (16.1 ng/mL) and to low-risk individuals (∼7.5 ng/mL). Dosing simulations indicated that high-risk women require full adherence to maintain protective levels., Conclusions: Using the largest PK-HIV outcome database to date, we developed a population adherence-PK-risk-outcome model. Our results indicate that high-risk females need higher levels of plasma TFV to achieve HIV protection compared with males. HIV protection exceeds 90% in all populations if daily adherence is achieved., Competing Interests: Potential conflicts of interest. D. V. G. has served on an Advisory Board for Merck and has personal fees from Gilead. C. W. H. contracts for clinical research, paid to Hopkins and unrelated to this work, from Gilead, Merck, and ViiV Healthcare; consulting fees from Gilead (scientific Advisory Board, travel support, paid to author), Merck (scientific Advisory Board, travel support and honoraria, paid to author), and ViiV Healthcare (scientific Advisory Board, travel support and honoraria, paid to author); US patents (2 issued patents related to HIV prevention technology); and a leadership role as founder of Prionde Biopharma, LLC (company to develop human immunodeficiency virus (HIV) prevention product). P. J. reports grants or contracts unrelated to this work: T32 GM007546 from the National Institute of General Medical Sciences (NIGMS). R. G. reports grants or contracts unrelated to this work from Gilead Sciences: employer, UCSF, has received funding to support work as a site investigator for clinical trials related to preexposure prophylaxis using agents other than FTC/TDF; and payment for expert testimony from the US Department of Justice (related to a patent held by the US Government related to preexposure prophylaxis using tenofovir esters and emtricitabine). C. L. C. reports consulting fees as a scientific advisor to Merck and Gilead Sciences. J. M. B. reports grants to institution, unrelated to this work, from NIH and BMGF and is an employee of Gilead Sciences (salary, stock, options). J. M. reports consulting fees and participation on Scientific Advisory Board from Merck and Gilead Sciences and is treasurer and board member for the Infectious Disease Society of America. P. A. reports contracts or grants unrelated to this work from Gilead Sciences (paid to institution); and consulting fees paid to author from Gilead Sciences, Merck, and ViiV. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The World Health Organization recommends pre-exposure prophylaxis (PrEP) for individuals at substantial risk of HIV infection. The aim of this analysis is to quantify the individual risk of HIV infection over time, using a large database of high-risk individuals (n = 5583). We used data from placebo recipients in five phase III PrEP trials: iPrEx, conducted in men who have sex with men and transgender women; VOICE, conducted in young women at high sexual risk; Partners PrEP, conducted in HIV serodiscordant heterosexual couples; TDF2, conducted in high-risk heterosexual men and women; and BTS, conducted in persons who inject drugs. The probability of HIV infection over time was estimated using NONMEM7.4. We identified predictors of HIV risk and found a substantial difference in the risk of infection among and within trial populations, with each study including a mix of low, moderate, and high-risk individuals (p < 0.05). Persons who were female at birth were at a higher risk of HIV infection than people who were male at birth. Final models were integrated in a tool that can assess person-specific risk and simulate cumulative HIV risk over time. These models can be used to optimize future PrEP clinical trials by identifying potential participants at highest risk.

Murine tuberculosis drug efficacy studies have historically monitored bacterial burden based on CFU of Mycobacterium tuberculosis in lung homogenate. In an alternative approach, a recently described molecular pharmacodynamic marker called the RS ratio quantifies drug effect on a fundamental cellular process, ongoing rRNA synthesis. Here, we evaluated the ability of different pharmacodynamic markers to distinguish between treatments in three BALB/c mouse experiments at two institutions. We confirmed that different pharmacodynamic markers measure distinct biological responses. We found that a combination of pharmacodynamic markers distinguishes between treatments better than any single marker. The combination of the RS ratio with CFU showed the greatest ability to recapitulate the rank order of regimen treatment-shortening activity, providing proof of concept that simultaneous assessment of pharmacodynamic markers measuring different properties will enhance insight gained from animal models and accelerate development of new combination regimens. These results suggest potential for a new era in which antimicrobial therapies are evaluated not only on culture-based measures of bacterial burden but also on molecular assays that indicate how drugs impact the physiological state of the pathogen.

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. To decrease the impact of expected variabilityin drug intake on tuberculosis outcomes, an improvement in patient adherence and new forgiving regimens that protect against missed doses are needed. In this review, we summarize emerging technologies to improve medication adherence in clinical practice and provide suggestions on how digital adherence technologies can be incorporated in clinical trials and practice and the drug development pipeline that will lead to more forgiving regimens and benefit patients suffering from tuberculosis.

The missense variant, breast cancer resistance protein (BCRP) p.Q141K, which encodes a reduced function BCRP, has been linked to poor response to allopurinol. Using a multifaceted approach, we aimed to characterize the relationship(s) between BCRP p.Q141K, the pharmacokinetics (PK) and pharmacodynamics (PD) of oxypurinol (the active metabolite of allopurinol), and serum uric acid (SUA) levels. A prospective clinical study (NCT02956278) was conducted in which healthy volunteers were given a single oral dose of 300 mg allopurinol followed by intensive blood sampling. Data were analyzed using noncompartmental analysis and population PK/PD modeling. Additionally, electronic health records were analyzed to investigate whether clinical inhibitors of BCRP phenocopied the effects of the p.Q141K variant with respect to SUA. Subjects homozygous for p.Q141K had a longer half-life (34.2 ± 12.2 h vs. 19.1 ± 1.42 h) of oxypurinol. The PK/PD model showed that women had a 24.8% lower volume of distribution. Baseline SUA was affected by p.Q141K genotype and renal function; that is, it changed by 48.8% for every 1 mg/dl difference in serum creatinine. Real-world data analyses showed that patients prescribed clinical inhibitors of BCRP have higher SUA levels than those that have not been prescribed inhibitors of BCRP, consistent with the idea that BCRP inhibitors phenocopy the effects of p.Q141K on uric acid levels. This study identified important covariates of oxypurinol PK/PD that could affect its efficacy for the treatment of gout as well as a potential side effect of BCRP inhibitors on increasing uric acid levels, which has not been described previously., (© 2021 The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of the American Society for Clinical Pharmacology and Therapeutics.)

Background: Selenite is a radiosensitizer and inhibitor of androgen receptor expression and function. In a phase I study (NCT02184533) in 15 subjects with metastatic cancer receiving daily oral sodium selenite with palliative radiation therapy, disease stabilization was observed, as evidenced by tumor regression, marked reduction in pain symptoms, and decreased prostate-specific antigen levels (only patients with castrate-resistant prostate cancer)., Objective: The aim of this work was to characterize the pharmacokinetics of selenite to suggest dosing strategies and to propose a study design for further investigation., Methods: With selenium plasma concentrations obtained from five dosing cohorts (5.5, 11, 16.5, 33, and 49.5 mg), a population pharmacokinetic model was constructed using NONMEM. The model described externally administered selenite (inorganic) with a baseline component for endogenous selenium levels. Using the pharmacokinetic model, simulations were performed to suggest dosing regimens that achieved in vitro target selenite levels, and optimal pharmacokinetic sampling times for a subsequent study were proposed using PopED., Results: A one-compartment model characterized selenite pharmacokinetics. Parameter estimates were absorption rate constant (0.64 h -1 ), apparent clearance (1.58 L/h), apparent volume of distribution (42.3 L), and baseline selenium amount (5270 μg). A logarithmic function characterized the inverse relationship between dose level and bioavailability. Four regimens to reach in vitro target selenite levels were proposed: 33 mg daily, 16.5 mg twice daily (BID), 11 mg BID, and 5.5 mg thrice daily (TID). Optimal sampling times were 1, 2, 6, and 24 h., Discussion: The population model described the pharmacokinetic data well. Three regimens (33 mg daily, 11 mg BID, 5.5 mg TID) achieved in vitro target selenite levels after one dose. The model and optimal sampling times may inform future studies evaluating the efficacy of selenite for metastatic cancer treatment.

There is urgent need for new drug regimens that more rapidly cure tuberculosis (TB). Existing TB drugs and regimens vary in treatment-shortening activity, but the molecular basis of these differences is unclear, and no existing assay directly quantifies the ability of a drug or regimen to shorten treatment. Here, we show that drugs historically classified as sterilizing and non-sterilizing have distinct impacts on a fundamental aspect of Mycobacterium tuberculosis physiology: ribosomal RNA (rRNA) synthesis. In culture, in mice, and in human studies, measurement of precursor rRNA reveals that sterilizing drugs and highly effective drug regimens profoundly suppress M. tuberculosis rRNA synthesis, whereas non-sterilizing drugs and weaker regimens do not. The rRNA synthesis ratio provides a readout of drug effect that is orthogonal to traditional measures of bacterial burden. We propose that this metric of drug activity may accelerate the development of shorter TB regimens.

Defining tissue and plasma-specific prophylactic drug concentrations is central to pre-exposure prophylaxis product development for sexual transmission of HIV-1. Pharmacokinetic (PK) data from study RMP-02/MTN-006 comparing single dose oral tenofovir disoproxil fumarate with single and multiple dose rectal tenofovir (TFV) gel administration in HIV-1 seronegative adults was used to construct a multicompartment plasma-rectal tissue population PK model for TFV and tenofovir-diphosphate (TFVdp) in plasma and rectal tissue. PK data were collected in five matrices: TFV (plasma, rectal tissue homogenate), TFVdp (peripheral blood mononuclear cells, rectal mononuclear cells (MMCs), rectal tissue homogenate). A viral growth compartment and a delayed effect compartment for p24 antigen expression measured from an ex vivo explant assay described HIV-1 infection and replication. Using a linear PK/pharmacodynamic model, MMC TFVdp levels over 9,000 fmol/million cells in the explant assay provided apparent viral replication suppression down to 1%. Parameters were estimated using NONMEM version 7.4., (© 2021 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of the American Society for Clinical Pharmacology and Therapeutics.)

Hydroxychloroquine (HCQ) is a promising candidate for Coronavirus disease of 2019 (COVID-19) treatment. The optimal dosing of HCQ is unknown. Our goal was to integrate historic and emerging pharmacological and toxicity data to understand safe and efficacious HCQ dosing strategies for COVID-19 treatment. The data sources included were (i) longitudinal clinical, pharmacokinetic (PK), and virologic data from patients with severe acute respiratory syndrome-2 (SARS-CoV-2) infection who received HCQ with or without azithromycin (n = 116), (ii) in vitro viral replication data and SARS-CoV-2 viral load inhibition by HCQ, (iii) a population PK model of HCQ, and (iv) a model relating chloroquine PKs to corrected QT (QTc) prolongation. A mechanistic PK/virologic/QTc model for HCQ was developed and externally validated to predict SARS-CoV-2 rate of viral decline and QTc prolongation. SARS-CoV-2 viral decline was associated with HCQ PKs (P < 0.001). The extrapolated patient half-maximal effective concentration (EC 50 ) was 4.7 µM, comparable to the reported in vitro EC 50s . HCQ doses > 400 mg b.i.d. for ≥5 days were predicted to rapidly decrease viral loads, reduce the proportion of patients with detectable SARS-CoV-2 infection, and shorten treatment courses, compared with lower dose (≤ 400 mg daily) regimens. However, HCQ doses > 600 mg b.i.d. were also predicted to prolong QTc intervals. This prolongation may have clinical implications warranting further safety assessment. Due to COVID-19's variable natural history, lower dose HCQ regimens may be indistinguishable from controls. Evaluation of higher HCQ doses is needed to ensure adequate safety and efficacy., (© 2020 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The aim of this work is to build a mechanistic multiscale pharmacokinetic model for the anticancer drug 2',2'-difluorodeoxycytidine (gemcitabine, dFdC), able to describe the concentrations of dFdC metabolites in the pancreatic tumor tissue in dependence of physiological and genetic patient characteristics, and, more in general, to explore the capabilities and limitations of this kind of modeling strategy. A mechanistic model characterizing dFdC metabolic pathway (metabolic network) was developed using in vitro literature data from two pancreatic cancer cell lines. The network was able to describe the time course of extracellular and intracellular dFdC metabolites concentrations. Moreover, a physiologically-based pharmacokinetic model was developed to describe clinical dFdC profiles by using enzymatic and physiological information available in the literature. This model was then coupled with the metabolic network to describe the dFdC active metabolite profile in the pancreatic tumor tissue. Finally, global sensitivity analysis was performed to identify the parameters that mainly drive the interindividual variability for the area under the curve (AUC) of dFdC in plasma and of its active metabolite (dFdCTP) in tumor tissue. From this analysis, cytidine deaminase (CDA) concentration was identified as the main driver of plasma dFdC AUC interindividual variability, whereas CDA and deoxycytidine kinase concentration mainly explained the tumor dFdCTP AUC variability. However, the lack of in vitro and in vivo information needed to characterize key model parameters hampers the development of this kind of mechanistic approach. Further studies to better characterize pancreatic cell lines and patient enzymes polymorphisms are encouraged to refine and validate the current model., (© 2020 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of the American Society for Clinical Pharmacology and Therapeutics.)

Background: Linezolid is increasingly important for multidrug-resistant tuberculosis (MDR-TB) treatment. However, among children with MDR-TB, there are no linezolid pharmacokinetic data, and its adverse effects have not yet been prospectively described. We characterised the pharmacokinetics, safety, and optimal dose of linezolid in children treated for MDR-TB., Methods and Findings: Children routinely treated for MDR-TB in 2 observational studies (2011-2015, 2016-2018) conducted at a single site in Cape Town, South Africa, underwent intensive pharmacokinetic sampling after either a single dose or multiple doses of linezolid (at steady state). Linezolid pharmacokinetic parameters, and their relationships with covariates of interest, were described using nonlinear mixed-effects modelling. Children receiving long-term linezolid as a component of their routine treatment had regular clinical and laboratory monitoring. Adverse events were assessed for severity and attribution to linezolid. The final population pharmacokinetic model was used to derive optimal weight-banded doses resulting in exposures in children approximating those in adults receiving once-daily linezolid 600 mg. Forty-eight children were included (mean age 5.9 years; range 0.6 to 15.3); 31 received a single dose of linezolid, and 17 received multiple doses. The final pharmacokinetic model consisted of a one-compartment model characterised by clearance (CL) and volume (V) parameters that included allometric scaling to account for weight; no other evaluated covariates contributed to the model. Linezolid exposures in this population were higher compared to exposures in adults who had received a 600 mg once-daily dose. Consequently simulated, weight-banded once-daily optimal doses for children were lower than those currently used for most weight bands. Ten of 17 children who were followed long term had a linezolid-related adverse event, including 5 with a grade 3 or 4 event, all anaemia. Adverse events resulted in linezolid dose reductions in 4, temporary interruptions in 5, and permanent discontinuation in 4 children. Limitations of the study include the lack of very young children (none below 6 months of age), the limited number who were HIV infected, and the modest number of children contributing to long-term safety data., Conclusions: Linezolid-related adverse effects were frequent and occasionally severe. Careful linezolid safety monitoring is required. Compared to doses currently used in children in many settings for MDR-TB treatment, lower doses may approximate current adult target exposures, might result in fewer adverse events, and should therefore be evaluated., Competing Interests: The authors have declared that no competing interests exist.

The aim of this evaluation was to predict tumour response to gemcitabine in patients with advanced pancreas or ovarian cancer using pre-clinical data obtained from xenograft tumour-bearing mice. The approach consisted of building a translational model combining pre-clinical pharmacokinetic-pharmacodynamic (PKPD) models and parameters, with dosing paradigms used in the clinics along with clinical PK models to derive tumour profiles in humans driving overall survival. Tumour growth inhibition simulations were performed using drug effect parameters obtained from mice, system parameters obtained from mice after appropriate scaling, patient PK models for gemcitabine and carboplatin, and the standard dosing schedules given in the clinical scenario for both types of cancers. Tumour profiles in mice were scaled by body weight to their equivalent values in humans. As models for survival in humans showed that tumour size was the main driver of the hazard rate, it was possible to describe overall survival in pancreatic and ovarian cancer patients. Simulated tumour dynamics in pancreatic and ovarian cancer patients were evaluated using available data from clinical trials. Furthermore, calculated metrics showed values (maximal tumour regression [0-17%] and tumour size ratio at week 12 with respect to baseline [- 9, - 4.5]) in the range of those predicted with the clinical PKPD models. The model-informed Drug Discovery and Development paradigm has been successfully applied retrospectively to gemcitabine data, through a semi-mechanistic translational approach, describing the time course of the tumour response in patients from pre-clinical studies.

Xenograft mice are largely used to evaluate the efficacy of oncological drugs during preclinical phases of drug discovery and development. Mathematical models provide a useful tool to quantitatively characterize tumor growth dynamics and also optimize upcoming experiments. To the best of our knowledge, this is the first report where unperturbed growth of a large set of tumor cell lines ( n = 28) has been systematically analyzed using a previously proposed model of nonlinear mixed effects (NLME). Exponential growth was identified as the governing mechanism in the majority of the cell lines, with constant rate values ranging from 0.0204 to 0.203 day -1 No common patterns could be observed across tumor types, highlighting the importance of combining information from different cell lines when evaluating drug activity. Overall, typical model parameters were precisely estimated using designs in which tumor size measurements were taken every 2 days. Moreover, reducing the number of measurements to twice per week, or even once per week for cell lines with low growth rates, showed little impact on parameter precision. However, a sample size of at least 50 mice is needed to accurately characterize parameter variability (i.e., relative S.E. values below 50%). This work illustrates the feasibility of systematically applying NLME models to characterize tumor growth in drug discovery and development, and constitutes a valuable source of data to optimize experimental designs by providing an a priori sampling window and minimizing the number of samples required., (Copyright © 2018 by The American Society for Pharmacology and Experimental Therapeutics.)

The aim of this evaluation was to characterize the impact of the tumour size (TS) effects driven by the anticancer drug gemcitabine on overall survival (OS) in patients with advanced pancreatic cancer by building and validating a predictive semi-mechanistic joint TS-OS model. TS and OS data were obtained from one phase II and one phase III study where gemcitabine was administered (1000-1250 mg/kg over 30-60 min i.v infusion) as single agent to patients (n = 285) with advanced pancreatic cancer. Drug exposure, TS and OS were linked using the population approach with NONMEM 7.3. Pancreatic tumour progression was characterized by exponential growth (doubling time = 67 weeks), and tumour response to treatment was described as a function of the weekly area under the gemcitabine triphosphate concentration vs time curve (AUC), including treatment-related resistance development. The typical predicted percentage of tumour growth inhibition with respect to no treatment was 22.3% at the end of 6 chemotherapy cycles. Emerging resistance elicited a 57% decrease in drug effects during the 6th chemotherapy cycle. Predicted TS profile was identified as main prognostic factor of OS, with tumours responders' profiles improving median OS by 30 weeks compared to stable-disease TS profiles. Results of NCT00574275 trial were predicted using this modelling framework, thereby validating the approach as a prediction tool in clinical development. Our analyses show that despite the advanced stage of the disease in this patient population, the modelling framework herein can be used to predict the likelihood of treatment success using early clinical data., (Copyright © 2018 Elsevier B.V. All rights reserved.)

In this work, a semimechanistic tumor growth-response model for gemcitabine in pancreatic (administered as single agent) and ovarian (given as single agent and in combination with carboplatin) cancer in mice was developed. Tumor profiles were obtained from nude mice, previously inoculated with KP4, ASPC1, MIA PACA2, PANC1 (pancreas), A2780, or SKOV3×luc (ovarian) cell lines, and then treated with different dosing schedules of gemcitabine and/or carboplatin. Data were fitted using the population approach with Nonlinear Mixed Effect Models 7.2. In addition to cell proliferation, the tumor progression model for both types of cancer incorporates a carrying capacity representing metabolite pool for DNA synthesis required to tumor growth. Analysis of data from the treated groups revealed that gemcitabine exerted its tumor effects by promoting apoptosis as well as decreasing the carrying capacity compartment. Pharmacodynamic parameters were cell-specific and overall had similar range values between cancer types. In pancreas, a linear model was used to describe both gemcitabine effects with parameter values between 3.26 × 10 -2 and 4.2 × 10 -1 L/(mg × d). In ovarian cancer, the apoptotic effect was driven by an E MAX model with an efficacy/potency ratio of 5.25-8.65 L/(mg × d). The contribution of carboplatin to tumor effects was lower than the response exerted by gemcitabine and was incorporated in the model as an inhibition of the carrying capacity. The model developed was consistent in its structure across different tumor cell lines and two tumor types where gemcitabine is approved. Simulation-based evaluation diagnostics showed that the model performed well in all experimental design scenarios, including dose, schedule, and tumor type., (Copyright © 2017 by The American Society for Pharmacology and Experimental Therapeutics.)