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Noncompartmental analysis (NCA) is a model-independent approach for assessing pharmacokinetics (PKs). Although the existing NCA algorithms are very well-established and widely utilized, they suffer from low accuracies in the setting of sparse PK samples. In response, we developed Deep-NCA, a deep learning (DL) model to improve the prediction of key noncompartmental PK parameters. Our methodology utilizes synthetic PK data for model training and uses an innovative patient-specific normalization method for data preprocessing. Deep-NCA demonstrated adequate performance across six previously unseen simulated drugs under multiple dosing, showcasing effective generalization. Compared to traditional NCA, Deep-NCA exhibited superior performance for sparse PK data. This study advances the application of DL to PK studies and introduces an effective method for handling sparse PK data. With further validation and refinement, Deep-NCA could significantly enhance the efficiency of drug development by providing more accurate NCA estimates while requiring fewer PK samples., (© 2024 Genentech, Inc. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Nilotinib, a second‐generation tyrosine kinase inhibitor (TKI), has been approved in the United States and Europe as a treatment for patients with newly diagnosed chronic myeloid leukemia (CML)‐chronic phase (CP) and patients with CML‐CP or chronic myeloid leukemia‐accelerated phase (CML‐AP) who are resistant or intolerant to imatinib (a first‐generation TKI). This study compared the bioequivalence and safety of the test nilotinib capsule and reference nilotinib capsule (Tasigna, Novartis) in healthy Chinese volunteers under fasting conditions for marketing authorization in China. The results of the study are reported for the first time. This was a single‐dose, randomized, open‐label, two‐period, and cross‐over study. Thirty healthy volunteers were randomly assigned to receive a single dose of a 200‐mg test or reference capsule under fasting conditions in each period with a 10‐day washout. Plasma samples were analyzed with liquid chromatography‐tandem mass spectrometry. Pharmacokinetic parameters were calculated with WinNonlin software. The geometric mean ratio and the corresponding 90% confidence intervals of Cmax, AUC0‐t, and AUC0‐∞ for nilotinib between the two fixed‐dose combination formulations were within the bioequivalence acceptance range of 80%–125%, therefore the generic and branded formulations were bioequivalent in healthy Chinese volunteers. [ABSTRACT FROM AUTHOR]

[Display omitted] The favorable benefit–risk profile of polatuzumab vedotin, as demonstrated in a pivotal Phase Ib/II randomized study (GO29365; NCT02257567), coupled with the need for effective therapies in relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL), prompted the need to accelerate polatuzumab vedotin development. An integrated, fit-for-purpose clinical pharmacology package was designed to support regulatory approval. To address key clinical pharmacology questions without dedicated clinical pharmacology studies, we leveraged non-clinical and clinical data for polatuzumab vedotin, published clinical data for brentuximab vedotin, a similar antibody–drug conjugate, and physiologically based pharmacokinetic and population pharmacokinetic modeling approaches. We review strategies and model-informed outcomes that contributed to regulatory approval of polatuzumab vedotin plus bendamustine and rituximab in R/R DLBCL. These strategies made polatuzumab vedotin available to patients earlier than previously possible; depending on the strength of available data and the regulatory/competitive environment, they may also prove useful in accelerating the development of other agents. [ABSTRACT FROM AUTHOR]

Purpose: The established two-analyte integrated population pharmacokinetic model was applied to assess the impact of intrinsic/extrinsic factors on the pharmacokinetics (PK) of polatuzumab vedotin (pola) in patients with non-Hodgkin lymphoma (NHL) following bodyweight-based dosing. Methods: Model simulations based on individual empirical Bayes estimates were used to evaluate the impact of intrinsic/extrinsic factors as patient subgroups on Cycle 6 exposures. Intrinsic factors included bodyweight, age, sex, hepatic and renal functions. Extrinsic factors included rituximab/obinutuzumab or bendamustine combination with pola and manufacturing process. The predicted impact on exposures along with the established exposure-response relationships were used to assess clinical relevance. Results: No clinically meaningful differences in Cycle 6 pola exposures were found for the following subgroups: bodyweight 100–146 kg versus 38–<100 kg, age ≥ 65 years versus <65 years, female versus male, mild hepatic impairment versus normal, mild-to-moderate renal impairment versus normal. Co-administration of rituximab/obinutuzumab or bendamustine, and change in the pola manufacturing process, also had no meaningful impact on PK. Conclusions: In patients with NHL, bodyweight-based dosing is adequate, and no further dose adjustment is recommended for the heavier subgroup (100–146 kg). In addition, no dose adjustments are recommended for other subgroups based on intrinsic/extrinsic factors evaluated. [ABSTRACT FROM AUTHOR]

Exposure-response relationships were investigated to assess the risk/benefit of polatuzumab vedotin (pola) + bendamustine-rituximab (pola + BR) in relapsed/refractory diffuse large B-cell lymphoma (R/R DLBCL). Analyses were conducted in pivotal study GO29365 (NCT02257567; BR/pola + BR/pola + BG [BG: bendamustine-obinutuzumab]; 1.8 mg/kg pola, every 3 weeks [Q3W], six cycles), and supportive studies DCS4968g (NCT01290549) and GO27834 (NCT01691898) (pola/pola + R/pola + G; 0.1–2.4 mg/kg pola Q3W; eight-cycle landmark), separately. Exposure was characterized as simulated cycle-6 AUC and Cmax for antibody-conjugated mono-methyl auristatin E (acMMAE) and unconjugated MMAE. Supportive studies showed response rate and safety risk (grade ≥2 peripheral neuropathy; grade ≥3 anemia) increased with exposure, suggesting not to dose below 1.8 mg/kg (up to eight-cycle) for balancing safety and efficacy. Pivotal study with limited exposure range showed no exposure-safety relationship and slightly positive exposure (acMMAE)-efficacy relationship for overall survival. The exposure-response analyses and the observed risk/benefit characteristics in pivotal study supported pola (1.8 mg/kg) +BR Q3W for six cycles in R/R DLBCL patients. [ABSTRACT FROM AUTHOR]

Purpose: The CD79b-targeted antibody–drug conjugate polatuzumab vedotin (pola), alone and with chemoimmunotherapy, has clinical efficacy and a tolerable safety profile in B-cell non-Hodgkin lymphoma (B-NHL). We assessed (a) whether exposure from global studies of pola is comparable to Asian patients, and (b) if the recommended pola dose is appropriate in Asian patients based on exposure. Methods: The pharmacokinetics (PK) of pola in Asian and global populations was characterized for three analytes (antibody-conjugated monomethyl auristatin E (MMAE) [acMMAE], total antibody, and unconjugated MMAE) in five phase 1b/2 single-agent and combination studies in B-NHL patients (JO29138 [JAPICCTI‐142580], DCS4968g [NCT01290549], GO27834 [NCT01691898], GO29044 [NCT01992653], and GO29365 [NCT02257567]). PK data were compared between Japanese phase 1 JO29138 (JAPICCTI‐142580) and global phase 1 DCS4968g (NCT01290549) studies and between Asian and non-Asian patients in the randomized relapsed/refractory B-NHL cohorts of the phase 1b/2 study GO29365 (NCT02257567). A population PK (popPK) model was used to assess the effects of Asian race and region on acMMAE and unconjugated MMAE exposure. Results: PK non-compartmental analysis (NCA) parameters for the key analyte acMMAE in the Japanese JO29138 (JAPICCTI‐142580) and global phase 1 DCS4968g (NCT01290549) studies were similar. In GO29365 (NCT02257567), the phase 1b/2 combination study, mean exposure to the analytes was generally lower in Asian patients (by ~ 9.9 to 17.5%), but not to a clinically meaningful extent. Overall, the popPK model further suggested comparable PK in Asian patients with B-NHL (race or region) versus non-Asian patients. Conclusion: Race has no clinically meaningful effect on pola PK. These results (and observations from efficacy/safety exposure–response analyses) support no pola dose adjustments are warranted for Asian patients with DLBCL. [ABSTRACT FROM AUTHOR]

Background: Venetoclax is a selective B-cell lymphoma-2 (BCL-2) inhibitor approved for use as monotherapy or with rituximab in patients with chronic lymphocytic leukemia (CLL). The objectives of the current analysis of observed data from adult patients randomized to venetoclax-rituximab in the phase III MURANO study were to characterize venetoclax pharmacokinetics (PKs) using a Bayesian approach, evaluate whether a previously developed population PK model for venetoclax can describe the PKs of venetoclax when administered with rituximab, and to determine post hoc estimates of PK parameters for the exposure-response analysis.Methods: Parameter estimates and uncertainty estimated by a population PK model were used as priors. Additional covariate effects (CLL risk status, geographic region, and 17p deletion [del(17p)] status) were added to the model. The updated model was used to describe venetoclax PKs after repeated dosing in combination with rituximab, and to determine post hoc estimates of PK parameters for exposure-response analysis.Results: The PK analysis included 600 quantifiable venetoclax PK samples from 182 patients in the MURANO study. Model evaluation using standard diagnostic plots, visual predictive checks, and normalized prediction distribution error plots indicated no model deficiencies. There was no significant relationship between venetoclax apparent clearance (CL/F) and bodyweight, age, sex, mild and moderate hepatic and renal impairment, or coadministration of weak cytochrome P450 3A inhibitors. The chromosomal abnormality del(17p) and CLL risk status had no apparent effect on the PKs of venetoclax. A minimal increase in venetoclax CL/F (approximately 7%) was observed after coadministration with rituximab. CL/F was 30% lower in patients from Central and Eastern Europe (n = 60) or Asia (n = 4) compared with other regions (95% confidence interval [CI] 21-39%). Apparent central volume of distribution was 30% lower (95% CI 22-38%) in females (n = 56) compared with males (n = 126). No clinically significant impact of region or sex was observed on key safety and efficacy outcomes.Conclusions: The Bayesian model successfully characterized venetoclax PKs over time and confirmed key covariates affecting PKs in the MURANO study. The model was deemed appropriate for further use in simulations and for generating individual patient PK parameters for subsequent exposure-response evaluation. [ABSTRACT FROM AUTHOR]

Prediction of human pharmacokinetics (PK) based on preclinical information for antibody–drug conjugates (ADCs) provide important insight into first‐in‐human (FIH) study design. This retrospective analysis was conducted to identify an appropriate scaling method to predict human PK for ADCs from animal PK data in the linear range. Different methods for projecting human clearance (CL) from animal PK data for 11 ADCs exhibiting linear PK over the tested dose ranges were examined: multiple species allometric scaling (CL vs. body weight), allometric scaling with correction factors, allometric scaling based on rule of exponent, and scaling from only cynomolgus monkey PK data. Two analytes of interest for ADCs, namely total antibody and conjugate (measured as conjugated drug or conjugated antibody), were assessed. Percentage prediction errors (PEs) and residual sum of squares (RSS) were compared across methods. Human CL was best estimated using cynomolgus monkey PK data alone and an allometric scaling exponent of 1.0 for CL. This was consistently observed for both conjugate and total antibody analytes. Other scaling methods either underestimated or overestimated human CL, or produced larger average absolute PEs and RSS. Human concentration‐time profiles were also reasonably predicted from the cynomolgus monkey data using species‐invariant time method with a fixed exponent of 1.0 for CL and 1.0 for volume of distribution. In conclusion, results from this retrospective analysis of 11 ADCs indicate that allometric scaling of CL with an exponent of 1.0 using cynomolgus monkey PK data alone can successfully project human PK profiles of an ADC within linear range. [ABSTRACT FROM AUTHOR]

Abstract: A rapid and precise liquid chromatography coupled with hybrid ion trap/time‐of‐flight mass spectrometry method to detect and quantify caulophine and its possible active metabolites in rat plasma and urine was developed. Samples were prepared by plasma protein precipitation combined with a liquid‐liquid extraction method. The separation was carried out on an InertSustain® C18 column with a mobile phase comprising methanol and 0.1% aqueous formic acid solution. The analysis was complete in 20 min with a flow rate of 0.4 mL/min. Taspine was used as the internal standard. Mass spectrometric detection was conducted with hybrid ion trap/time‐of‐flight equipped with electrospray ionization in the positive ion mode. The calibration curves of caulophine were linear over the concentration ranges of 0.002–0.20 μg/mL for plasma and 0.005–0.50 μg/mL for urine with the correlation coefficients greater than 0.998 in both cases. The method was successfully used to investigate the pharmacokinetics and bioavailability in rat plasma and urine samples after intragastric and intraperitoneal administration of caulophine sodium salt. [ABSTRACT FROM AUTHOR]

Background and Objectives: Monomethyl auristatin E (MMAE, a cytotoxic agent), upon releasing from valine-citrulline-MMAE (vc-MMAE) antibody-drug conjugates (ADCs), is expected to behave like small molecules. Therefore, evaluating the drug-drug interaction (DDI) potential associated with MMAE is important in the clinical development of ADCs. The objective of this work was to build a physiologically based pharmacokinetic (PBPK) model to assess MMAE-drug interactions for vc-MMAE ADCs. Methods: A PBPK model linking antibody-conjugated MMAE (acMMAE) to its catabolite unconjugated MMAE associated with vc-MMAE ADCs was developed using a mixed 'bottom-up' and 'top-down' approach. The model was developed using in silico and in vitro data and in vivo pharmacokinetic data from anti-CD22-vc-MMAE ADC. Subsequently, the model was validated using clinical pharmacokinetic data from another vc-MMAE ADC, brentuximab vedotin. Finally, the verified model was used to simulate the results of clinical DDI studies between brentuximab vedotin and midazolam, ketoconazole, and rifampicin. Results: The pharmacokinetic profile of acMMAE and unconjugated MMAE following administration of anti-CD22-vc-MMAE was well described by simulations using the developed PBPK model. The model's performance in predicting unconjugated MMAE pharmacokinetics was verified by successful simulation of the pharmacokinetic profile following brentuximab vedotin administration. The model simulated DDIs, expressed as area under the concentration-time curve (AUC) and maximum concentration ( C) ratios, were well within the two-fold of the observed data from clinical DDI studies. Conclusions: This work is the first demonstration of the use of PBPK modelling to predict MMAE-based DDI potential. The described model can be extended to assess the DDI potential of other vc-MMAE ADCs. [ABSTRACT FROM AUTHOR]

Background and Objective: Trastuzumab emtansine (T-DM1) is an antibody-drug conjugate recently approved by the US Food and Drug Administration for the treatment of human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer previously treated with trastuzumab and taxane chemotherapy. It comprises the microtubule inhibitory cytotoxic agent DM1 conjugated to the HER2-targeted humanized monoclonal antibody trastuzumab via a stable linker. To characterize the pharmacokinetics of T-DM1 in patients with metastatic breast cancer, concentrations of multiple analytes were quantified, including serum concentrations of T-DM1 conjugate and total trastuzumab (the sum of conjugated and unconjugated trastuzumab), as well as plasma concentrations of DM1. The clearance of T-DM1 conjugate is approximately 2 to 3 times faster than its parent antibody, trastuzumab. However, the clearance pathways accounting for this faster clearance rate are unclear. An integrated population pharmacokinetic model that simultaneously fits the pharmacokinetics of T-DM1 conjugate and total trastuzumab can help to elucidate the clearance pathways of T-DM1. The model can also be used to predict total trastuzumab pharmacokinetic profiles based on T-DM1 conjugate pharmacokinetic data and sparse total trastuzumab pharmacokinetic data, thereby reducing the frequency of pharmacokinetic sampling. Methods: T-DM1 conjugate and total trastuzumab serum concentration data, including baseline trastuzumab concentrations prior to T-DM1 treatment, from phase I and II studies were used to develop this integrated population pharmacokinetic model. Based on a hypothetical T-DM1 catabolism scheme, two-compartment models for T-DM1 conjugate and trastuzumab were integrated by assuming a one-step deconjugation clearance from T-DM1 conjugate to trastuzumab. The ability of the model to predict the total trastuzumab pharmacokinetic profile based on T-DM1 conjugate pharmacokinetics and various sampling schemes of total trastuzumab pharmacokinetics was assessed to evaluate total trastuzumab sampling schemes. Results: The final model reflects a simplified catabolism scheme of T-DM1, suggesting that T-DM1 clearance pathways include both deconjugation and proteolytic degradation. The model fits T-DM1 conjugate and total trastuzumab pharmacokinetic data simultaneously. The deconjugation clearance of T-DM1 was estimated to be ~0.4 L/day. Proteolytic degradation clearances for T-DM1 and trastuzumab were similar (~0.3 L/day). This model accurately predicts total trastuzumab pharmacokinetic profiles based on T-DM1 conjugate pharmacokinetic data and sparse total trastuzumab pharmacokinetic data sampled at preinfusion and end of infusion in cycle 1, and in one additional steady state cycle. Conclusions: This semi-mechanistic integrated model links T-DM1 conjugate and total trastuzumab pharmacokinetic data, and supports the inclusion of both proteolytic degradation and deconjugation as clearance pathways in the hypothetical T-DM1 catabolism scheme. The model attributes a faster T-DM1 conjugate clearance versus that of trastuzumab to the presence of a deconjugation process and suggests a similar proteolytic clearance of T-DM1 and trastuzumab. Based on the model and T-DM1 conjugate pharmacokinetic data, a sparse pharmacokinetic sampling scheme for total trastuzumab provides an entire pharmacokinetic profile with similar predictive accuracy to that of a dense pharmacokinetic sampling scheme. [ABSTRACT FROM AUTHOR]

Purpose: Trastuzumab emtansine (T-DM1) is an antibody-drug conjugate comprising trastuzumab and DM1, a microtubule polymerization inhibitor, covalently bound via a stable thioether linker. To characterize the pharmacokinetics (PK) of T-DM1 in patients with human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer, data from four studies (TDM3569g, TDM4258g, TDM4374g, and TDM4688g) of single-agent T-DM1 administered at 3.6 mg/kg every 3 weeks (q3w) were assessed in aggregate. Methods: Multiple analytes-T-DM1, total trastuzumab (TT), DM1, and key metabolites-were quantified using enzyme-linked immunosorbent assays or liquid chromatography tandem mass spectrometry. PK parameters of T-DM1, TT, and DM1 exposure were calculated using standard noncompartmental approaches and correlated to efficacy (objective response rate) and safety (platelet counts, hepatic transaminase concentrations). Immunogenicity was evaluated by measuring anti-therapeutic antibodies (ATA) to T-DM1 after repeated dosing using validated bridging antibody electrochemiluminescence or enzyme-linked immunosorbent assays. Results: PK parameters for T-DM1, TT, and DM1 were consistent across studies at cycle 1 and steady state. T-DM1 PK was not affected by residual trastuzumab from prior therapy or circulating extracellular domain of HER2. No significant correlations were observed between T-DM1 exposure and efficacy, thrombocytopenia, or increased concentrations of transaminases. Across the studies, ATA formation was detected in 4.5% (13/286) of evaluable patients receiving T-DM1 q3w. Conclusions: The PK profile of single-agent T-DM1 (3.6 mg/kg q3w) is predictable, well characterized, and unaffected by circulating levels of HER2 extracellular domain or residual trastuzumab. T-DM1 exposure does not correlate with clinical responses or key adverse events. [ABSTRACT FROM AUTHOR]

Background and Objective: Dosing of therapeutic monoclonal antibodies (mAbs) is often based on body size, with the perception that body size-based dosing would reduce inter-subject variability in drug exposure. However, most mAbs are target specific with a relatively large therapeutic window and generally a small contribution of body size to pharmacokinetic variability. Therefore, the dosing paradigm for mAbs should be assessed in the context of these unique characteristics. The objective of this study was to review the current dosing strategy and to provide a scientific rationale for dosing of mAbs using a modelling and simulation approach. Methods: In this analysis, the body weight-based or body weight-independent (fixed) dosing regimens for mAbs were systematically evaluated. A generic two-compartment first-order elimination model was developed. Individual or population pharmacokinetic profiles were simulated as a function of the body weight effects on clearance (θBW&lowbar;CL) and on the central volume of distribution (θBW&lowbar;VI). The variability in exposure (the area under the serum concentration-time curve [AUC], trough serum concentration [Cmin,] and peak serum concentration [Cmax]) was compared between body weight-based dosing and fixed dosing in the entire population. The deviation of exposure for light and heavy subjects from median body weight subjects was also measured. The simulation results were then evaluated with clinical pharmacokinetic characteristics of various mAbs that were given either by body weight-based dosing or by fixed dosing in the case study. Results: Results from this analysis demonstrated that exposure variability was dependent on the magnitude of the body weight effect on pharmacokinetics. In contrast to the conventional assumption, body weight-based dosing does not always offer advantages over fixed dosing in reducing exposure variability. In general, when the exponential functions of θBW&lowbar;CL and θBW&lowbar;VIl in the population pharmacokinetic model are <0.5, fixed dosing results in less variability and less deviation than body weight-based dosing; when both θBW&lowbar;CL and θBW&lowbar;VI are >0.5, body weight-based dosing results in less variability and less deviation than fixed dosing. In the scenarios when either θBW&lowbar;CL or θBW&lowbar;VI is >0.5, the impact on exposure variability is different for each exposure measure. The case study demonstrated that most mAbs had little effect or a moderate body weight effect (θBW&lowbar;CL and θBW&lowbar;VI <0.5 or ~0.5). The difference of variability in exposure between body weight-based and fixed dosing is generally less than 20% and the percentages of deviation for light and heavy subpopulations are less than 40%. Conclusions: The analysis provided insights into the conditions under which either fixed or body weight-based dosing would be superior in reducing pharmacokinetic variability and exposure differences between light and heavy subjects across the population. The pharmacokinetic variability introduced by either dosing regimen is moderate relative to the variability generally observed in pharmacodynamics, efficacy and safety. Therefore, mAb dosing can be flexible. Given many practical advantages, fixed dosing is recommended to be the first option in first-in-human studies with mAbs. The dosing strategy in later stages of clinical development could then be determined based on combined knowledge of the body weight effect on pharmacokinetics, safety and efficacy from the early clinical trials. [ABSTRACT FROM AUTHOR]

Abstract: A novel biological sample clean-up procedure has been developed for the determination of phosphorothioate oligodeoxynucleotides (PS-ODNs) and derived metabolites in biological fluids (plasma, urine and bile) and in tissues and feces from mice and rats. This method uses a one-step C18 solid-phase extraction (SPE) for biological matrix removal, and it uses capillary gel electrophoresis (CGE) for analyte detection. The assay is specific, and its linearity is superb (r >0.99) for IV-AS (a 13-mer PS-ODN) and PS19 (a 19-mer PS-ODN) in a variety of biological matrices. For both IV-AS and PS19, the precision, accuracy and absolute recovery values were found to be <20%, ±20% and 80–120%, respectively. The LODs of IV-AS and PS19 were 0.6mg/l for plasma, 0.8mg/l for rat urine and bile, 6μg/g for rat tissues, and 10μg/g for rat feces, with a signal-to-noise ratio of 3 (S/N =3). This method has been successfully applied to the analysis and quantitation of PS-ODNs in various biological samples arising from preclinical pharmacokinetic studies. [Copyright &y& Elsevier]