The usefulness of determining plasma and tissue concentrations of phosphorodiamidate morpholino oligonucleotides to estimate their efficacy in Duchenne muscular dystrophy patients.

Currently four kinds of phosphorodiamidate morpholino oligomers (PMOs) such as viltolarsen have been approved for the treatment of Duchenne muscular dystrophy (DMD); however, it is unclear whether human efficacy can be estimated using plasma concentrations. This study summarizes the tissue distribution of viltolarsen in mice and cynomolgus monkeys and evaluates the relationship between exposure and efficacy based on exon skipping. In the tissue distribution studies, all muscles in DMD model mice showed higher concentrations of viltolarsen than those in wild-type mice and cynomolgus monkeys, and the concentrations in skeletal muscle were correlated with the exon-skipping efficiency in mice and cynomolgus monkeys. In addition, a highly sensitive bioanalytical method using liquid chromatography with tandem mass spectrometry shows promise for determining plasma concentrations up to a later time point, and the tissue (muscle)/plasma concentration ratio (Kp) in DMD model mice was shown to be useful for predicting changes in pharmacodynamic (PD) markers in humans. Our results suggest that pharmacokinetic (PK)/PD analysis can be conducted by using the human PK profile or Kp values and skipping efficiency in DMD model mice. This information will be useful for the efficient and effective development of PMOs as therapeutic agents. Significance Statement We compare that plasma and tissue concentrations with the efficiency of exon skipping for viltolarsen as an example phosphorodiamidate morpholino oligomers in skeletal and cardiac muscle of mice and cynomolgus monkeys for pharmacokinetics/pharmacodynamics (PK/PD) analysis. Our results suggest that PK/PD analysis can be conducted by using the human PK profile or Kp values and skipping efficiency in DMD model mice.

Optimizing tylosin dosage for co-infection of Actinobacillus pleuropneumoniae and Pasteurella multocida in pigs using pharmacokinetic/pharmacodynamic modeling.

Formulating a therapeutic strategy that can effectively combat concurrent infections of Actinobacillus pleuropneumoniae (A. pleuropneumoniae) and Pasteurella multocida (P. multocida) can be challenging. This study aimed to 1) establish minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), time kill curve, and post-antibiotic effect (PAE) of tylosin against A. pleuropneumoniae and P. multocida pig isolates and employ the MIC data for the development of epidemiological cutoff (ECOFF) values; 2) estimate the pharmacokinetics (PKs) of tylosin following its intramuscular (IM) administration (20 mg/kg) in healthy and infected pigs; and 3) establish a PK-pharmacodynamic (PD) integrated model and predict optimal dosing regimens and PK/PD cutoff values for tylosin in healthy and infected pigs. The MIC of tylosin against both 89 and 363 isolates of A. pleuropneumoniae and P. multocida strains spread widely, ranging from 1 to 256 µg/mL and from 0.5 to 128 µg/mL, respectively. According to the European Committee on Antimicrobial Susceptibility Testing (EUCAST) ECOFFinder analysis ECOFF value (≤64 µg/mL), 97.75% (87 strains) of the A. pleuropnumoniae isolates were wild-type, whereas with the same ECOFF value (≤64 µg/mL), 99.72% (363 strains) of the P. multicoda isolates were considered wild-type to tylosin. Area under the concentration time curve (AUC), T1/2, and Cmax values were significantly greater in healthy pigs than those in infected pigs (13.33 h × µg/mL, 1.99 h, and 5.79 µg/mL vs. 10.46 h × µg/mL, 1.83 h, and 3.59 µg/mL, respectively) (p < 0.05). In healthy pigs, AUC24 h/MIC values for the bacteriostatic activity were 0.98 and 1.10 h; for the bactericidal activity, AUC24 h/MIC values were 1.97 and 1.99 h for A. pleuropneumoniae and P. multocida, respectively. In infected pigs, AUC24 h/MIC values for the bacteriostatic activity were 1.03 and 1.12 h; for bactericidal activity, AUC24 h/MIC values were 2.54 and 2.36 h for A. pleuropneumoniae and P. multocida, respectively. Monte Carlo simulation lead to a 2 µg/mL calculated PK/PD cutoff. Managing co-infections can present challenges, as it often demands the administration of multiple antibiotics to address diverse pathogens. However, using tylosin, which effectively targets both A. pleuropneumoniae and P. multocida in pigs, may enhance the control of bacterial burden. By employing an optimized dosage of 11.94-15.37 mg/kg and 25.17-27.79 mg/kg of tylosin can result in achieving bacteriostatic and bactericidal effects in 90% of co-infected pigs.

Population pharmacokinetic-pharmacodynamic analysis of givinostat.

BACKGROUND: Givinostat (ITF2357), an oral, synthetic histone deacetylase inhibitor, significantly improved all histological muscle biopsy parameters in a Phase II study in boys with Duchenne muscular dystrophy (DMD). RESEARCH DESIGN AND METHODS: A population pharmacokinetic (PK) model, including seven clinical studies, was developed to explore the effect of covariates on givinostat PK. The final model was qualified to simulate pediatric dosing recommendations. A PK/pharmacodynamic (PD) model was developed to simulate the link between givinostat plasma concentration and platelet time course in 10-70-kg children following 6 months of givinostat 20-70 mg twice daily. RESULTS: A two-compartment model, with first-order input with lag and first-order elimination from the central compartment, described givinostat PK, demonstrating increasing apparent clearance with increasing body weight. The PK/PD model well-described platelet count time course. Weight-based dosing (arithmetic mean systemic exposure of 554-641 ng·h/mL) produced an average platelet count decrease from baseline of 45% with maximum decrease within 28 days. After 1 week and 6 months, ~1% and ~14-15% of patients, respectively, had a platelet count <75 × 109/L. CONCLUSIONS: Based on these data, givinostat dosing will be body weight adjusted and include monitoring of platelet counts to support efficacy and safety in a Phase III DMD study.

Modeling the Impact of a Highly Potent Plasmodium falciparum Transmission-Blocking Monoclonal Antibody in Areas of Seasonal Malaria Transmission.

Transmission-blocking interventions can play an important role in combating malaria worldwide. Recently, a highly potent Plasmodium falciparum transmission-blocking monoclonal antibody (TB31F) was demonstrated to be safe and efficacious in malaria-naive volunteers. Here we predict the potential public health impact of large-scale implementation of TB31F alongside existing interventions. We developed a pharmaco-epidemiological model, tailored to 2 settings of differing transmission intensity with already established insecticide-treated nets and seasonal malaria chemoprevention interventions. Community-wide annual administration (at 80% coverage) of TB31F over a 3-year period was predicted to reduce clinical incidence by 54% (381 cases averted per 1000 people per year) in a high-transmission seasonal setting, and 74% (157 cases averted per 1000 people per year) in a low-transmission seasonal setting. Targeting school-aged children gave the largest reduction in terms of cases averted per dose. An annual administration of the transmission-blocking monoclonal antibody TB31F may be an effective intervention against malaria in seasonal malaria settings.

How can machine learning and multiscale modeling benefit ocular drug development?

The eyes possess sophisticated physiological structures, diverse disease targets, limited drug delivery space, distinctive barriers, and complicated biomechanical processes, requiring a more in-depth understanding of the interactions between drug delivery systems and biological systems for ocular formulation development. However, the tiny size of the eyes makes sampling difficult and invasive studies costly and ethically constrained. Developing ocular formulations following conventional trial-and-error formulation and manufacturing process screening procedures is inefficient. Along with the popularity of computational pharmaceutics, non-invasive in silico modeling & simulation offer new opportunities for the paradigm shift of ocular formulation development. The current work first systematically reviews the theoretical underpinnings, advanced applications, and unique advantages of data-driven machine learning and multiscale simulation approaches represented by molecular simulation, mathematical modeling, and pharmacokinetic (PK)/pharmacodynamic (PD) modeling for ocular drug development. Following this, a new computer-driven framework for rational pharmaceutical formulation design is proposed, inspired by the potential of in silico explorations in understanding drug delivery details and facilitating drug formulation design. Lastly, to promote the paradigm shift, integrated in silico methodologies were highlighted, and discussions on data challenges, model practicality, personalized modeling, regulatory science, interdisciplinary collaboration, and talent training were conducted in detail with a view to achieving more efficient objective-oriented pharmaceutical formulation design.

Machine Learning for Pharmacokinetic/Pharmacodynamic Modeling.

A variety of new recurrent neural networks (RNNs) including the ODE-LSTM, Phased LSTM, CTGRU and GRU-D, were evaluated on modeling irregularly sampled PK/PD data with 6 or 12 time points/day and predicting PD data of unseen dosing regimens and dosing levels. The one-compartment absorption PK model and the Indirect PK/PD model I was used to simulate the PK/PD with inter-individual variabilities in volume of distribution and residual errors in PD measurement. The four RNNs were able to successfully model daily dose (QD) PK/PD and extrapolate to twice daily (BID) dose PD based on BID PK. The RNNs not only captured the additional fluctuations in the BID regimen but also the return phase to the baseline PD. However, extrapolating to unseen dose levels outside of the dose range for training proved to be challenging for all the RNNs tested. Only the GRUD demonstrated reasonable prediction results when extrapolating to unseen doses that were 3 or 10-fold outside the training doses. Overall, these new RNNs were able to overcome some limitations of previous RNNs evaluated and showed promise of integrating neural networks in PK/PD.

Latent variable indirect response modeling of clinical efficacy endpoints with combination therapy: application to guselkumab and golimumab in patients with ulcerative colitis.

Accurate characterization of longitudinal exposure-response of clinical trial endpoints is important in optimizing dose and dosing regimens in drug development. Clinical endpoints are often categorical, for which much progress has been made recently in latent variable indirect response (IDR) modeling with single drugs. However, such applications have not yet been used for trials employing multiple drugs administered concurrently. This study aims to demonstrate that the latent variable IDR approach provides a convenient longitudinal exposure-response modeling framework to assess potential interaction effects of combination therapies. This is illustrated by an application to the exposure-response modeling of guselkumab, a monoclonal antibody in clinical development that blocks the interleukin-23p19 subunit, and golimumab, a monoclonal antibody that binds with high affinity to tumor necrosis factor-alpha. A Phase 2a study was conducted in 214 patients with moderate-to severe active ulcerative colitis for which longitudinal assessments of disease severity based on patient-reported measures of rectal bleeding, stool frequency, and symptomatic remission were evaluated as categorical endpoints, and fecal calprotectin as a continuous endpoint. The modeling results suggested independent pharmacodynamic guselkumab and golimumab effects on fecal calprotectin as a continuous endpoint, as well as interaction effects on the categorical endpoints that may be explained by an additional pathway of competitive interaction.

Application of Pharmacokinetic/Pharmacodynamic Modeling to Bridge Mouse Antitumor Efficacy and Monkey Toxicology Data for Determining the Therapeutic Index of an Interleukin-10 Fc Fusion Protein.

Pharmacokinetic/pharmacodynamic (PK/PD) modeling was performed to quantitatively integrate preclinical pharmacology and toxicology data for determining the therapeutic index (TI) of an interleukin-10 (IL-10) fragment crystallizable (Fc) fusion protein. Mouse Fc fused with mouse IL-10 (mFc-mIL-10) was studied in mice for antitumor efficacy, and the elevation of interleukin-18 (IL-18) was examined as a PD biomarker. The in vivo mFc-mIL-10 EC50 for the IL-18 induction was estimated to be 2.4 nM, similar to the in vitro receptor binding affinity (Kd) of 3.2 nM. The IL-18 induction was further evaluated in cynomolgus monkeys, where the in vivo induction EC50 by a human IL-10 human Fc-fusion protein (hFc-hIL-10) was 0.08 nM vs. 0.3 nM measured as the in vitro Kd. The extent of the IL-18 induction correlated with mouse antitumor efficacy and was used to connect mouse efficacy to that in monkeys. The PD-based efficacious dose projected in monkeys was comparable to the results obtained using a PK-based method in which mouse efficacious exposure was targeted and corrected for affinity differences between the species. Furthermore, PK/PD relationships were developed for anemia and thrombocytopenia in monkeys treated with hFc-hIL-10, with thrombocytopenia predicted to be dose-limiting toxicity. Using quantitative pharmacology and toxicology information obtained through modeling work in the same species, the TI of hFc-hIL-10 in monkeys was determined to be 2.4 (vs. PD-based efficacy) and 1.2-3 (vs. PK-based efficacy), indicating a narrow safety margin. The model-based approaches were proven valuable to the developability assessment of the IL-10 Fc-fusion protein.

Establishing PK Equivalence Between Adalimumab and ABP 501 in the Presence of Antidrug Antibodies Using Population PK Modeling.

PURPOSE: ABP 501 (European Union, adalimumab; United States, adalimumab-atto) is a biosimilar to the adalimumab reference product (RP). A model was developed characterizing population pharmacokinetic (PK) variables of ABP 501 and adalimumab RP to include the impact of antidrug antibodies (ADAs). METHODS: Data were retrospectively analyzed from a single-dose, parallel-group bioequivalence study in healthy adults who received a single 40-mg SC injection of ABP 501 or adalimumab RP. Modeling was performed by using NONMEM 7.2. The impact of ADAs on PK similarity was assessed from population model-based AUC0-∞ values using ANCOVA. FINDINGS: Linear compartment models with various clearance pathways were compared with a one-compartment distribution, first-order subcutaneous absorption model. The final model, a one-compartment model with first-order subcutaneous absorption and linear clearance from the central compartment with an additional time-dependent linear clearance for ADA-positive subjects, described ABP 501 and adalimumab RP population PK variables. Model-derived estimates confirmed PK similarity for ABP 501 and adalimumab RP despite the impact of ADAs. IMPLICATIONS: A traditional approach for evaluating bioequivalence based on noncompartmental analysis may be inappropriate for drugs with a high incidence of ADAs because accounting for the effect of ADAs on noncompartmental analysis parameters is challenging. Use of a population PK model to discern the effect of ADAs on drug PK variables allows for assessment of PK similarity accounting for the presence or absence of ADAs.

Population Pharmacokinetics of Amikacin in Patients on Veno-Arterial Extracorporeal Membrane Oxygenation.

Veno-arterial extracorporeal membrane oxygenation (V-A ECMO) support leads to complex pharmacokinetic alterations, whereas adequate drug dosing is paramount for efficacy and absence of toxicity in critically ill patients. Amikacin is a major antibiotic used in nosocomial sepsis, especially for these patients. We aimed to describe amikacin pharmacokinetics on V-A ECMO support and to determine relevant variables to improve its dosing. All critically ill patients requiring empirical antimicrobial therapy, including amikacin for nosocomial sepsis supported or not by V-A ECMO, were included in a prospective population pharmacokinetic study. This population pharmacokinetic analysis was built with a dedicated software, and Monte Carlo simulations were performed to identify doses achieving therapeutic plasma concentrations. Thirty-nine patients were included (control n = 15, V-A ECMO n = 24); 215 plasma assays were performed and used for the modeling process. Patients received 29 (24-33) and 32 (30-35) mg/kg of amikacin in control and ECMO groups, respectively. Data were best described by a two-compartment model with first-order elimination. Inter-individual variabilities were observed on clearance, central compartment volume (V1), and peripherical compartment volume (V2). Three significant covariates explained these variabilities: Kidney Disease Improving Global Outcomes (KDIGO) stage on amikacin clearance, total body weight on V1, and ECMO support on V2. Our simulations showed that the adequate dosage of amikacin was 40 mg/kg in KDIGO stage 0 patients, while 25 mg/kg in KDIGO stage 3 patients was relevant. V-A ECMO support had only a secondary impact on amikacin pharmacokinetics, as compared to acute kidney injury.

Quantifying the Pharmacodynamics of Morphine in the Treatment of Postoperative Pain in Preverbal Children.

While the pharmacokinetics of morphine in children have been studied extensively, little is known about the pharmacodynamics of morphine in this population. Here, we quantified the concentration-effect relationship of morphine for postoperative pain in preverbal children between 0 and 3 years of age. For this, we applied item response theory modeling in the pharmacokinetic/pharmacodynamic analysis of COMFORT-Behavior (COMFORT-B) scale data from 2 previous clinical studies. In the model, we identified a sigmoid maximal efficacy model for the effect of morphine and found that in 26% of children, increasing morphine concentrations were not associated with lower pain scores (nonresponders to morphine up-titration). In responders to morphine up-titration, the COMFORT-B score slowly decreases with increasing morphine concentrations at morphine concentrations >20 ng/mL. In nonresponding children, no decrease in COMFORT-B score is expected. In general, lower baseline COMFORT-B scores (2.1 points on average) in younger children (postnatal age <10.3 days) were found. Based on the model, we conclude that the percentage of children at a desirable COMFORT-B score is maximized at a morphine concentration between 5 and 30 ng/mL for children aged <10 days, and between 5 and 40 ng/mL for children >10 days. These findings support a dosing regimen previously suggested by Krekels et al, which would put >95% of patients within this morphine target concentration range at steady state. Our modeling approach provides a promising platform for pharmacodynamic research of analgesics and sedatives in children.

Piperaquine-Induced QTc Prolongation Decreases With Repeated Monthly Dihydroartemisinin-Piperaquine Dosing in Pregnant Ugandan Women.

BACKGROUND: Intermittent preventive treatment with monthly dihydroartemisinin-piperaquine (DHA-PQ) is highly effective at preventing both malaria during pregnancy and placental malaria. Piperaquine prolongs the corrected QT interval (QTc), and it is possible that repeated monthly dosing could lead to progressive QTc prolongation. Intensive characterization of the relationship between piperaquine concentration and QTc interval throughout pregnancy can inform effective, safe prevention guidelines. METHODS: Data were collected from a randomized controlled trial, where pregnant Ugandan women received malaria chemoprevention with monthly DHA-PQ (120/960 mg DHA/PQ; n = 373) or sulfadoxine-pyrimethamine (SP; 1500/75 mg; n = 375) during the second and third trimesters of pregnancy. Monthly trough piperaquine samples were collected throughout pregnancy, and pre- and postdose electrocardiograms were recorded at 20, 28, and 36 weeks' gestation in each woman. The pharmacokinetics-QTc relationship for piperaquine and QTc for SP were assessed using nonlinear mixed-effects modeling. RESULTS: A positive linear relationship between piperaquine concentration and Fridericia corrected QTc interval was identified. This relationship progressively decreased from a 4.42 to 3.28 to 2.13 millisecond increase per 100 ng/mL increase in piperaquine concentration at 20, 28, and 36 weeks' gestation, respectively. Furthermore, 61% (n = 183) of women had a smaller change in QTc at week 36 than week 20. Nine women given DHA-PQ had grade 3-4 cardiac adverse events. SP was not associated with any change in QTc. CONCLUSIONS: Repeated DHA-PQ dosing did not result in increased risk of QTc prolongation and the postdose QTc intervals progressively decreased. Monthly dosing of DHA-PQ in pregnant women carries minimal risk of QTc prolongation. CLINICAL TRIALS REGISTRATION: NCT02793622.

Improving categorical endpoint longitudinal exposure-response modeling through the joint modeling with a related endpoint.

Exposure-response modeling is important to optimize dose and dosing regimens in clinical drug development. While primary clinical trial endpoints often have few categories and thus provide only limited information, sometimes there may be additional, more informative endpoints. Benefits of fully incorporating relevant information in longitudinal exposure-response modeling through joint modeling have recently been shown. This manuscript aims to further investigate the benefit of joint modeling of an ordered categorical primary endpoint with a related near-continuous endpoint, through the sharing of model parameters in the latent variable indirect response (IDR) modeling framework. This is illustrated by analyzing the data collected through up to 116 weeks from a phase 3b response-adaptive trial of ustekinumab in patients with psoriasis. The primary endpoint was based on the 6-point physician's global assessment (PGA) score. The Psoriasis area and severity Index (PASI) data, ranging from 0 to 72 with 0.1 increments, were also available. Separate and joint latent variable Type I IDR models of PGA and PASI scores were developed and compared. The results showed that the separate PGA model had a substantial structural bias, which was corrected by the joint modeling of PGA and PASI scores.

Development and Validation of an In Silico Decision Tool To Guide Optimization of Intravenous Artesunate Dosing Regimens for Severe Falciparum Malaria Patients.

Most deaths from severe falciparum malaria occur within 24 h of presentation to a hospital. Intravenous (i.v.) artesunate is the first-line treatment for severe falciparum malaria, but its efficacy may be compromised by delayed parasitological responses. In patients with severe malaria, the life-saving benefit of the artemisinin derivatives is their ability to clear circulating parasites rapidly, before they can sequester and obstruct the microcirculation. To evaluate the dosing of i.v. artesunate for the treatment of artemisinin-sensitive and reduced ring stage sensitivity to artemisinin severe falciparum malaria infections, Bayesian pharmacokinetic-pharmacodynamic modeling of data from 94 patients with severe malaria (80 children from Africa and 14 adults from Southeast Asia) was performed. Assuming that delayed parasite clearance reflects a loss of ring stage sensitivity to artemisinin derivatives, the median (95% credible interval) percentage of patients clearing ≥99% of parasites within 24 h (PC24≥99%) for standard (2.4 mg/kg body weight i.v. artesunate at 0 and 12 h) and simplified (4 mg/kg i.v. artesunate at 0 h) regimens was 65% (52.5% to 74.5%) versus 44% (25% to 61.5%) for adults, 62% (51.5% to 74.5%) versus 39% (20.5% to 58.5%) for larger children (≥20 kg), and 60% (48.5% to 70%) versus 36% (20% to 53.5%) for smaller children (<20 kg). The upper limit of the credible intervals for all regimens was below a PC24≥99% of 80%, a threshold achieved on average in clinical studies of severe falciparum malaria infections. In severe falciparum malaria caused by parasites with reduced ring stage susceptibility to artemisinin, parasite clearance is predicted to be slower with both the currently recommended and proposed simplified i.v. artesunate dosing regimens.

Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling to Support Waivers of In Vivo Clinical Studies: Current Status, Challenges, and Opportunities.

Physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling has been extensively applied to quantitatively translate invitro data, predict the invivo performance, and ultimately support waivers of invivo clinical studies. In the area of biopharmaceutics and within the context of model-informed drug discovery and development (MID3), there is a rapidly growing interest in applying verified and validated mechanistic PBPK models to waive invivo clinical studies. However, the regulatory acceptance of PBPK analyses for biopharmaceutics and oral drug absorption applications, which is also referred to variously as "PBPK absorption modeling" [Zhang et al. CPT: Pharmacometrics Syst. Pharmacol. 2017, 6, 492], "physiologically based absorption modeling", or "physiologically based biopharmaceutics modeling" (PBBM), remains rather low [Kesisoglou et al. J. Pharm. Sci. 2016, 105, 2723] [Heimbach et al. AAPS J. 2019, 21, 29]. Despite considerable progress in the understanding of gastrointestinal (GI) physiology, invitro biopharmaceutic and in silico tools, PBPK models for oral absorption often suffer from an incomplete understanding of the physiology, overparameterization, and insufficient model validation and/or platform verification, all of which can represent limitations to their translatability and predictive performance. The complex interactions of drug substances and (bioenabling) formulations with the highly dynamic and heterogeneous environment of the GI tract in different age, ethnic, and genetic groups as well as disease states have not been yet fully elucidated, and they deserve further research. Along with advancements in the understanding of GI physiology and refinement of current or development of fully mechanistic in silico tools, we strongly believe that harmonization, interdisciplinary interaction, and enhancement of the translational link between invitro, in silico, and invivo will determine the future of PBBM. This Perspective provides an overview of the current status of PBBM, reflects on challenges and knowledge gaps, and discusses future opportunities around PBPK/PD models for oral absorption of small and large molecules to waive invivo clinical studies.

Pharmacokinetic and Pharmacodynamic Modeling of Tezepelumab to Guide Phase 3 Dose Selection for Patients With Severe Asthma.

Tezepelumab is a human monoclonal antibody that blocks thymic stromal lymphopoietin, an epithelial cytokine involved in asthma pathogenesis. In the phase 2b PATHWAY study (ClinicalTrials.gov identifier: NCT02054130), tezepelumab significantly reduced exacerbations in adults with severe, uncontrolled asthma. We used pharmacokinetic (PK) and pharmacodynamic (PD) modeling to guide tezepelumab dose selection for phase 3 trials in patients with severe asthma. PK data from 7 clinical studies were used to develop a population PK model. Population PK-PD models were developed to characterize the relationship between tezepelumab PK and asthma exacerbation rate (AER) and fractional exhaled nitric oxide (FeNO) levels (using phase 2b PD data only). Tezepelumab PK were well described by a 2-compartment model with first-order absorption; PK parameter estimates were consistent with those of other immunoglobulin G2 antibodies. PK-PD models predicted that subcutaneous dosing at 210 mg every 4 weeks was associated with ≈90% of the maximum drug effect of tezepelumab on AER and FeNO; further dose increases were not expected to result in additional, clinically meaningful treatment benefit. No clinically significant covariates of treatment effects on AER and FeNO were identified. Population PK simulations, exposure-response relationships and safety profiles of tezepelumab at doses up to 280 mg every 2 weeks suggested that no dose adjustment based on body weight or for adolescents was required. These results support the selection of 210 mg every 4 weeks subcutaneously as the dose for phase 3 studies of tezepelumab in adults and adolescents with severe asthma.

Model-Informed Precision Dosing: Background, Requirements, Validation, Implementation, and Forward Trajectory of Individualizing Drug Therapy.

Model-informed precision dosing (MIPD) has become synonymous with modern approaches for individualizing drug therapy, in which the characteristics of each patient are considered as opposed to applying a one-size-fits-all alternative. This review provides a brief account of the current knowledge, practices, and opinions on MIPD while defining an achievable vision for MIPD in clinical care based on available evidence. We begin with a historical perspective on variability in dose requirements and then discuss technical aspects of MIPD, including the need for clinical decision support tools, practical validation, and implementation of MIPD in health care. We also discuss novel ways to characterize patient variability beyond the common perceptions of genetic control. Finally, we address current debates on MIPD from the perspectives of the new drug development, health economics, and drug regulations.

Population Pharmacodynamic Modeling Using the Sigmoid Emax Model: Influence of Inter-individual Variability on the Steepness of the Concentration-Effect Relationship. a Simulation Study.

The relationship between the concentration of a drug and its pharmacological effect is often described by empirical mathematical models. We investigated the relationship between the steepness of the concentration-effect relationship and inter-individual variability (IIV) of the parameters of the sigmoid Emax model, using the similarity between the sigmoid Emax model and the cumulative log-normal distribution. In addition, it is investigated whether IIV in the model parameters can be estimated accurately by population modeling. Multiple data sets, consisting of 40 individuals with 4 binary observations in each individual, were simulated with varying values for the model parameters and their IIV. The data sets were analyzed using Excel Solver and NONMEM. An empirical equation (Eq. (11)) was derived describing the steepness of the population-predicted concentration-effect profile (γ*) as a function of γ and IIV in C50 and γ, and was validated for both binary and continuous data. The tested study design is not suited to estimate the IIV in C50 and γ with reasonable precision. Using a naive pooling procedure, the population estimates γ* are significantly lower than the value of γ used for simulation. The steepness of the population-predicted concentration-effect relationship (γ*) is less than that of the individuals (γ). Using γ*, the population-predicted drug effect represents the drug effect, for binary data the probability of drug effect, at a given concentration for an arbitrary individual.

Application of Beta-Distribution and Combined Uniform and Binomial Methods in Longitudinal Modeling of Bounded Outcome Score Data.

Disease status is often measured with bounded outcome scores (BOS) which takes a discrete set of values on a finite range. The distribution of such data is often skewed, rendering the standard analysis methods assuming normal distribution inappropriate. Among the methods used for BOS analyses, two of them have the ability to predict the data within its natural range and accommodate data skewness: (1) a recently proposed beta-distribution based approach and (2) a mixture model known as CUB (combined uniform and binomial). This manuscript compares the two approaches, using an established mechanism-based longitudinal exposure-response model to analyze data from a phase 2 clinical trial in psoriatic patients. The beta-distribution-based approach was confirmed to perform well, and CUB also showed potential. A separate issue of modeling clinical trial data is that the collected baseline disease score range may be more limited than that of post-treatment disease score due to clinical trial inclusion criteria, a fact that is typically ignored in longitudinal modeling. The effect of baseline disease status restriction should in principle be adjusted for in longitudinal modeling.

Facilitating Longitudinal Exposure-Response Modeling of a Composite Endpoint Using the Joint Modeling of Sparsely and Frequently Collected Subcomponents.

Longitudinal exposure-response modeling plays an important role in optimizing dose and dosing regimens in clinical drug development. Certain clinical trials contain induction and maintenance phases where the maintenance treatment depends on the subjects' achieving the main endpoint outcome in the induction phase. Due to logistic difficulties and cost considerations, the main endpoint is usually collected more sparsely than a subcomponent (or other related endpoints). The sparse collection of the main endpoint hampers its longitudinal modeling. In principle, the frequent collection of a subcomponent allows its longitudinal modeling. However, the model evaluation via the visual predictive check (VPC) in the maintenance phase is difficult due to the requirement of the main-endpoint model to identify the treatment subgroups. This manuscript proposes a solution to this dilemma via the joint modeling of the main endpoint and the subcomponent. The challenges are illustrated by analyzing the data collected up to 60 weeks from a phase III trial of ustekinumab in patients with moderate-to-severe ulcerative colitis (UC). The main endpoint Mayo score, a commonly used composite endpoint to measure the severity of UC, was collected only at baseline, the end of the induction phase, and the end of the maintenance phase. The partial Mayo score, which is a major subset of the Mayo score, was collected at nearly every 4 weeks. A longitudinal joint exposure-response model, developed under a latent-variable Indirect Response modeling framework, described the Mayo score time course and facilitated the VPC model evaluation under a response-adaptive trial design.