AAPS JournalPub Date : 2024-06-11DOI: 10.1208/s12248-024-00937-3
Anna Kopp, Jiakun Guan, Colette Johnston, Steven Vance, James Legg, Laurie Galson-Holt, Greg M Thurber
{"title":"Design of Crosslinking Antibodies For T-Cell Activation: Experimental and Computational Analysis of PD-1/CD137 Bispecific Agents.","authors":"Anna Kopp, Jiakun Guan, Colette Johnston, Steven Vance, James Legg, Laurie Galson-Holt, Greg M Thurber","doi":"10.1208/s12248-024-00937-3","DOIUrl":"10.1208/s12248-024-00937-3","url":null,"abstract":"<p><p>Bispecific and multispecific agents have become increasingly utilized in cancer treatment and immunotherapy, yet their complex design parameters present a challenge in developing successful therapeutics. Bispecifics that crosslink receptors on two opposing cells can provide specific activation of a receptor only when these cells are in close spatial proximity, such as an immune cell and cancer cell in a tumor. These agents, including T cell activating bispecifics, can avoid off-tumor toxicity through activation only in the tumor microenvironment by utilizing a tumor target to cluster T-cell receptors for a selective costimulatory signal. Here, we investigate a panel of PD-1/CD137 targeted Humabody V<sub>H</sub> domains to determine the key factors for T cell activation, such as affinity, valency, expression level, domain orientation, and epitope location. Target expression is a dominant factor determining both specificity and potency of T cell activation. Given an intrinsic expression level, the affinity can be tuned to modulate the level of activation and IC<sub>50</sub> and achieve specificity between low and high expression levels. Changing the epitope location and linker length showed minor improvements to activation at low expression levels, but increasing the valency for the target decreased activation at all expression levels. By combining non-overlapping epitopes for the target, we achieved higher receptor activation at low expression levels. A kinetic model was able to capture these trends, offering support for the mechanistic interpretation. This work provides a framework to quantify factors for T cell activation by cell-crosslinking bispecific agents and guiding principles for the design of new agents.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"26 4","pages":"68"},"PeriodicalIF":5.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11497593/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141307265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AAPS JournalPub Date : 2024-06-06DOI: 10.1208/s12248-024-00928-4
John P Prybylski, Yuchen Wang, Vaishali Sahasrabudhe, Vivek Purohit
{"title":"Simulating Healthy Participant Pharmacokinetics for Renal and Hepatic Impairment Studies: Retrospective Assessment of the Approach.","authors":"John P Prybylski, Yuchen Wang, Vaishali Sahasrabudhe, Vivek Purohit","doi":"10.1208/s12248-024-00928-4","DOIUrl":"10.1208/s12248-024-00928-4","url":null,"abstract":"<p><p>The recruitment of a parallel, healthy participants (HPs) arm in renal and hepatic impairment (RI and HI) studies is a common strategy to assess differences in pharmacokinetics. Limitations in this approach include the underpowered estimate of exposure differences and the use of the drug in a population for which there is no benefit. Recently, a method was published by Purohit et. al. (2023) that leveraged prior population pharmacokinetic (PopPK) modeling-based simulation to infer the distribution of exposure ratios between the RI/HI arms and HPs. The approach was successful, but it was a single example with a robust model having several iterations of development and fitting to extensive HP data. To test in more studies and models at different stages of development, our catalogue of RI/HI studies was searched, and those with suitable properties and from programs with available models were analyzed with the simulation approach. There were 9 studies included in the analysis. Most studies were associated with models that would have been available at the time (ATT) of the study, and all had a current, final model. For 3 studies, the HP PK was not predicted well by the ATT (2) or final (1) models. In comparison to conventional analysis of variance (ANOVA), the simulation approach provided similar point estimates and confidence intervals of exposure ratios. This PopPK based approach can be considered as a method of choice in situations where the simulation of HP data would not be an extrapolation, and when no other complicating factors are present.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"26 4","pages":"65"},"PeriodicalIF":5.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141285282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AAPS JournalPub Date : 2024-06-06DOI: 10.1208/s12248-024-00933-7
Mélanie Guhl, Julie Bertrand, Lucie Fayette, François Mercier, Emmanuelle Comets
{"title":"Correction: Uncertainty Computation at Finite Distance in Nonlinear Mixed Effects Models-a New Method Based on Metropolis-Hastings Algorithm.","authors":"Mélanie Guhl, Julie Bertrand, Lucie Fayette, François Mercier, Emmanuelle Comets","doi":"10.1208/s12248-024-00933-7","DOIUrl":"10.1208/s12248-024-00933-7","url":null,"abstract":"","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"26 4","pages":"64"},"PeriodicalIF":5.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141285281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AAPS JournalPub Date : 2024-05-30DOI: 10.1208/s12248-024-00934-6
Innocent Gerald Asiimwe, Bonginkosi S'fiso Ndzamba, Samer Mouksassi, Goonaseelan Colin Pillai, Aurelie Lombard, Jennifer Lang
{"title":"Machine-Learning Assisted Screening of Correlated Covariates: Application to Clinical Data of Desipramine.","authors":"Innocent Gerald Asiimwe, Bonginkosi S'fiso Ndzamba, Samer Mouksassi, Goonaseelan Colin Pillai, Aurelie Lombard, Jennifer Lang","doi":"10.1208/s12248-024-00934-6","DOIUrl":"10.1208/s12248-024-00934-6","url":null,"abstract":"<p><p>Stepwise covariate modeling (SCM) has a high computational burden and can select the wrong covariates. Machine learning (ML) has been proposed as a screening tool to improve the efficiency of covariate selection, but little is known about how to apply ML on actual clinical data. First, we simulated datasets based on clinical data to compare the performance of various ML and traditional pharmacometrics (PMX) techniques with and without accounting for highly-correlated covariates. This simulation step identified the ML algorithm and the number of top covariates to select when using the actual clinical data. A previously developed desipramine population-pharmacokinetic model was used to simulate virtual subjects. Fifteen covariates were considered with four having an effect included. Based on the F1 score (an accuracy measure), ridge regression was the most accurate ML technique on 200 simulated datasets (F1 score = 0.475 ± 0.231), a performance which almost doubled when highly-correlated covariates were accounted for (F1 score = 0.860 ± 0.158). These performances were better than forwards selection with SCM (F1 score = 0.251 ± 0.274 and 0.499 ± 0.381 without/with correlations respectively). In terms of computational cost, ridge regression (0.42 ± 0.07 seconds/simulated dataset, 1 thread) was ~20,000 times faster than SCM (2.30 ± 2.29 hours, 15 threads). On the clinical dataset, prescreening with the selected ML algorithm reduced SCM runtime by 42.86% (from 1.75 to 1.00 days) and produced the same final model as SCM only. In conclusion, we have demonstrated that accounting for highly-correlated covariates improves ML prescreening accuracy. The choice of ML method and the proportion of important covariates (unknown a priori) can be guided by simulations.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"26 4","pages":"63"},"PeriodicalIF":5.0,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141181251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AAPS JournalPub Date : 2024-05-24DOI: 10.1208/s12248-024-00932-8
Niels Hendrickx, France Mentré, Andreas Traschütz, Cynthia Gagnon, Rebecca Schüle, Matthis Synofzik, Emmanuelle Comets
{"title":"Correction: Prediction of Individual Disease Progression Including Parameter Uncertainty in Rare Neurodegenerative Diseases: The Example of Autosomal-Recessive Spastic Ataxia Charlevoix Saguenay (ARSACS).","authors":"Niels Hendrickx, France Mentré, Andreas Traschütz, Cynthia Gagnon, Rebecca Schüle, Matthis Synofzik, Emmanuelle Comets","doi":"10.1208/s12248-024-00932-8","DOIUrl":"10.1208/s12248-024-00932-8","url":null,"abstract":"","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"26 4","pages":"62"},"PeriodicalIF":5.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141094357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AAPS JournalPub Date : 2024-05-15DOI: 10.1208/s12248-024-00931-9
Léa Sorret, Wei Han Tan, Senta Voss, Patrick Favrod, Pascal Chalus, Matthias Winzer
{"title":"Impact on Quality during In-Use Preparation of an Antibody Drug Conjugate with Eight Different Closed System Transfer Device Brands.","authors":"Léa Sorret, Wei Han Tan, Senta Voss, Patrick Favrod, Pascal Chalus, Matthias Winzer","doi":"10.1208/s12248-024-00931-9","DOIUrl":"10.1208/s12248-024-00931-9","url":null,"abstract":"<p><p>The aim of this study was to investigate the in-use compatibility of eight commercially available closed system transfer device brands (CSTDs) with a formulated model antibody drug conjugate (ADC). Overall, in-use simulated dosing preparation applying the CSTD systems investigated raised concerns for several product quality attributes. The incompatibilities observed were mainly associated with increased visible and subvisible particles formation as well as significant changes in holdup volumes. Visible and subvisible particles contained heterogeneous mixtures of particle classes, with the majority of subvisible particles associated with silicone oil leaching from CSTD systems during simulated dose preparation upon contact with the ADC formulation. These observations demonstrate that CSTD use may adversely impact product quality and delivered dose which could potentially lead to safety and efficacy concerns during administration. Other product quality attributes measured including turbidity, color, ADC recovery, and purity by size exclusion HPLC, did not show relevant changes. It is therefore strongly recommended to test and screen the compatibility of CSTDs with the respective ADC, in a representative in-use simulated administration setting, during early CMC development, i.e., well before the start of clinical studies, to include information about compatibility and to ensure that the CSTD listed in the manuals of preparation for clinical handling has been thoroughly assessed before human use.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"26 3","pages":"61"},"PeriodicalIF":5.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140946459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AAPS JournalPub Date : 2024-05-10DOI: 10.1208/s12248-024-00930-w
Jacob Felderman, Lila Ramaiah, Maria-Dolores Vazquez-Abad, Dean Messing, Ying Chen
{"title":"Anti-Drug Antibody Incidence Comparison of Therapeutic Proteins Administered Via Subcutaneous vs. Intravenous Route.","authors":"Jacob Felderman, Lila Ramaiah, Maria-Dolores Vazquez-Abad, Dean Messing, Ying Chen","doi":"10.1208/s12248-024-00930-w","DOIUrl":"10.1208/s12248-024-00930-w","url":null,"abstract":"<p><p>Subcutaneous (SC) administration of therapeutic proteins is perceived to pose higher risk of immunogenicity when compared with intravenous (IV) route of administration (RoA). However, systematic evaluations of clinical data to support this claim are lacking. This meta-analysis was conducted to compare the immunogenicity of the same therapeutic protein by IV and SC RoA. Anti-drug antibody (ADA) data and controlling variables for 7 therapeutic proteins administered by both IV and SC routes across 48 treatment groups were analyzed. RoA was the primary independent variable of interest while therapeutic protein, patient population, adjusted dose, and number of ADA samples were controlling variables. Analysis of variance was used to compare the ADA incidence between IV and SC RoA, while accounting for controlling variables and potential interactions. Subsequently, 10 additional therapeutic proteins with ADA data published for both IV and SC administration were added to the above 7 therapeutic proteins and were evaluated for ADA incidence. RoA had no statistically significant effect on ADA incidence for the initial dataset of 7 therapeutic proteins (p = 0.55). The only variable with a significant effect on ADA incidence was the therapeutic protein. None of the other controlling variables, including their interactions with RoA, was significant. When all data from the 17 therapeutic proteins were pooled, there was no statistically significant effect of RoA on ADA incidence (p = 0.81). In conclusion, there is no significant difference in ADA incidence between the IV and SC RoA, based on analysis of clinical ADA data from 17 therapeutic proteins.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"26 3","pages":"60"},"PeriodicalIF":5.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140904921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AAPS JournalPub Date : 2024-05-09DOI: 10.1208/s12248-024-00929-3
Tan Zhang, Elisa A M Calvier, Elke H J Krekels, Catherijne A J Knibbe
{"title":"Impact of Obesity on Hepatic Drug Clearance: What are the Influential Variables?","authors":"Tan Zhang, Elisa A M Calvier, Elke H J Krekels, Catherijne A J Knibbe","doi":"10.1208/s12248-024-00929-3","DOIUrl":"10.1208/s12248-024-00929-3","url":null,"abstract":"<p><p>Drug clearance in obese subjects varies widely among different drugs and across subjects with different severity of obesity. This study investigates correlations between plasma clearance (CLp) and drug- and patient-related characteristics in obese subjects, and evaluates the systematic accuracy of common weight-based dosing methods. A physiologically-based pharmacokinetic (PBPK) modeling approach that uses recent information on obesity-related changes in physiology was used to simulate CLp for a normal-weight subject (body mass index [BMI] = 20) and subjects with various severities of obesity (BMI 25-60) for hypothetical hepatically cleared drugs with a wide range of properties. Influential variables for CLp change were investigated. For each drug and obese subject, the exponent that yields perfect allometric scaling of CLp from normal-weight subjects was assessed. Among all variables, BMI and relative changes in enzyme activity resulting from obesity proved highly correlated with obesity-related CLp changes. Drugs bound to α1-acid glycoprotein (AAG) had lower CLp changes compared to drugs bound to human serum albumin (HSA). Lower extraction ratios (ER) corresponded to higher CLp changes compared to higher ER. The allometric exponent for perfect scaling ranged from -3.84 to 3.34 illustrating that none of the scaling methods performed well in all situations. While all three dosing methods are generally systematically accurate for drugs with unchanged or up to 50% increased enzyme activity in subjects with a BMI below 30 kg/m<sup>2</sup>, in any of the other cases, information on the different drug properties and severity of obesity is required to select an appropriate dosing method for individuals with obesity.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"26 3","pages":"59"},"PeriodicalIF":5.0,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140899978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AAPS JournalPub Date : 2024-05-06DOI: 10.1208/s12248-024-00927-5
Helmut Schütz, Divan A Burger, Erik Cobo, David D Dubins, Tibor Farkás, Detlew Labes, Benjamin Lang, Jordi Ocaña, Arne Ring, Anastasia Shitova, Volodymyr Stus, Michael Tomashevskiy
{"title":"Correction: Group-by-Treatment Interaction Effects in Comparative Bioavailability Studies.","authors":"Helmut Schütz, Divan A Burger, Erik Cobo, David D Dubins, Tibor Farkás, Detlew Labes, Benjamin Lang, Jordi Ocaña, Arne Ring, Anastasia Shitova, Volodymyr Stus, Michael Tomashevskiy","doi":"10.1208/s12248-024-00927-5","DOIUrl":"10.1208/s12248-024-00927-5","url":null,"abstract":"","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"26 3","pages":"58"},"PeriodicalIF":5.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140872420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AAPS JournalPub Date : 2024-04-23DOI: 10.1208/s12248-024-00905-x
Mélanie Guhl, Julie Bertrand, Lucie Fayette, François Mercier, Emmanuelle Comets
{"title":"Uncertainty Computation at Finite Distance in Nonlinear Mixed Effects Models-a New Method Based on Metropolis-Hastings Algorithm.","authors":"Mélanie Guhl, Julie Bertrand, Lucie Fayette, François Mercier, Emmanuelle Comets","doi":"10.1208/s12248-024-00905-x","DOIUrl":"10.1208/s12248-024-00905-x","url":null,"abstract":"<p><p>The standard errors (SE) of the maximum likelihood estimates (MLE) of the population parameter vector in nonlinear mixed effect models (NLMEM) are usually estimated using the inverse of the Fisher information matrix (FIM). However, at a finite distance, i.e. far from the asymptotic, the FIM can underestimate the SE of NLMEM parameters. Alternatively, the standard deviation of the posterior distribution, obtained in Stan via the Hamiltonian Monte Carlo algorithm, has been shown to be a proxy for the SE, since, under some regularity conditions on the prior, the limiting distributions of the MLE and of the maximum a posterior estimator in a Bayesian framework are equivalent. In this work, we develop a similar method using the Metropolis-Hastings (MH) algorithm in parallel to the stochastic approximation expectation maximisation (SAEM) algorithm, implemented in the saemix R package. We assess this method on different simulation scenarios and data from a real case study, comparing it to other SE computation methods. The simulation study shows that our method improves the results obtained with frequentist methods at finite distance. However, it performed poorly in a scenario with the high variability and correlations observed in the real case study, stressing the need for calibration.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"26 3","pages":"53"},"PeriodicalIF":4.5,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140900123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}