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Model‐informed drug development (MIDD) approaches have rapidly advanced in drug development in recent years. Additionally, the Prescription Drug User Fee Act (PDUFA) VI has specific commitments to further enhance MIDD. Tumor growth dynamic (TGD) modeling, as one of the commonly utilized MIDD approaches in oncology, fulfills the purposes to accelerate the drug development, to support new drug and biologics license applications, and to guide the market access. Increasing knowledge of TGD modeling methodologies, encouraging applications in clinical setting for patients’ survival, and complementing assessment of regulatory review for submissions, together fueled promising potentials for imminent enhancement of TGD in oncology. This review is to comprehensively summarize the history of TGD, and present case examples of the recent advance of TGD modeling (mixture model and joint model), as well as the TGD impact on regulatory decisions, thus illustrating challenges and opportunities. Additionally, this review presents the future perspectives for TGD approach.

AIM: Despite significant advances in morbidity and mortality outcomes, quality of life for people with haemophilia (PWH) remains compromised. Underrecognized and undertreated mental health disorders decrease quality of life; however, reports are inconsistent regarding the true prevalence of mental health disorders in PWH. METHODS: We conducted a systematic literature search of Ovid MEDLINE, EMBASE, Psychinfo, and the Cochrane Library, and hand searched the journal Haemophilia to identify records and subsequently conducted a meta-analysis to determine the prevalence of depression, anxiety, and attention deficit hyperactivity disorder (ADHD) in patients with congenital haemophilia. RESULTS: Our search strategy identified 2315 records, and 28 studies met eligibility criteria. Meta-analysis demonstrated that PWH are at increased risk of depression (odds ratio (OR) 2.45; 95% Confidence Interval (CI) 1.64–3.68), anxiety (OR 1.74, 95% CI 1.01 – 3.00), anxiety / depression (OR 2.60, 95% CI 2.35 – 2.87), and ADHD (OR 3.48, 95% CI 1.74 – 6.96). We found considerable heterogeneity among the studies likely due to differences in assessment tools, populations studied, and year of publication. This suggests that standardized tools to diagnose mental health disorders in PWH are needed. Additionally, high-quality studies investigating mental health disorders in PWH are necessary to adequately document the prevalence of these disorders. CONCLUSION: Overall, our meta-analysis suggests that the prevalence of depression, anxiety, and ADHD across decades is significantly increased in PWH compared to the general population.

Differences in the effect of gefitinib and chemotherapy on tumor burden in non‐small cell lung cancer remain to be fully understood. Using a Bayesian hierarchical model of tumor size dynamics, we estimated the rates of tumor growth and treatment resistance for patients in the Iressa Pan‐Asia Study study (NCT00322452). The following relationships characterize greater efficacy of gefitinib in epidermal growth factor receptor (EGFR) positive tumors: Maximum drug effect is, in decreasing order, gefitinib in EGFR‐positive, chemotherapy in EGFR‐positive, chemotherapy in EGFR‐negative, and gefitinib in EGFR‐negative tumors; the rate of resistance emergence is, in increasing order: gefitinib in EGFR positive, chemotherapy in EGFR positive, while each is plausibly similar to the rate in EGFR negative tumors, which are estimated with less certainty. The rate of growth is smaller in EGFR‐positive than in EGFR‐negative fully resistant tumors, regardless of treatment. The model can be used to compare treatment effects and resistance dynamics among different drugs.

One of the main barriers to explaining the functional significance of glycan-based changes in cancer is the natural epitope heterogeneity found on the surface of cancer cells. To help address this knowledge gap, we focused on designing synthetic tools to explore the role of tumor-associated glycans of MUC1 in the formation of metastasis via association with lectins. In this study, we have synthesized for the first time a MUC1-derived positional scanning synthetic glycopeptide combinatorial library (PS-SGCL) that vary in number and location of cancer-associated Tn antigen using the “tea bag” approach. The determination of the isokinetic ratios necessary for the equimolar incorporation of (glyco)amino acids mixtures to resin-bound amino acid was determined, along with developing an efficient protocol for on resin deprotection of O-acetyl groups. Enzyme-linked lectin assay was used to screen PS-SGCL against two plant lectins, Glycine max soybean agglutinin and Vicia villosa. The results revealed a carbohydrate density-dependent affinity trend and site-specific glycosylation requirements for high affinity binding to these lectins. Hence, PS-SGCLs provide a platform to systematically elucidate MUC1-lectin binding specificities, which in the long term may provide a rational design for novel inhibitors of MUC1–lectin interactions involved in tumor spread and glycopeptide-based cancer vaccines.

To evaluate the role of anti-viral monoclonal antibodies (mAbs) in reducing SARS-CoV-2 transmission and mortality, an agent-based model was developed that accounted for social contacts, movement/travel, disease progression, and viral shedding. The model was calibrated to mortality from October 2020 and April 2021 (aggressive pandemic phase). The model also projected an extended outlook to estimate mortality during a less aggressive phase (April to August 2021). Simulated scenarios evaluated mAbs for averting infections and deaths on top of vaccine and aggregated non-pharmaceutical interventions. mAbs were used as active treatment and as passive immunity for post-exposure prophylaxis (PEP). Rapid diagnostic testing paired with mAbs was evaluated as early Treatment-as-Prevention strategy. Sensitivity analyses determined impact of increasing mAb supply and vaccine rollout. Allocation of mAbs as PEP or targeting those ≥65 years provided the greatest incremental benefits, averting up to 17% and 41% more infections and deaths, respectively, than vaccine alone. Rapid testing for earlier diagnosis and mAb use amplified these benefits. The model was sensitive to mAb supply; doubling supply further reduced infections and mortality. mAbs continued to provide incremental benefits even as the proportion of the vaccinated population increased. Model projections estimated that ~42% of the expected deaths between April and August 2021 could be averted. Use of mAbs as early treatment and PEP on top of a vaccination program would substantially reduce SARS-CoV-2 transmission and mortality even as vaccination increases and overall mortality decreases. These results provide a template for informing public health policy for current and future pandemic preparedness.

As described in the ICH E5 guidelines, a bridging study is an additional study executed in a new geographical region or subpopulation to link or "build a bridge" from global clinical trial outcomes to the new region. The regulatory and scientific goals of a bridging study is to evaluate potential subpopulation differences while minimizing duplication of studies and meeting unmet medical needs expeditiously. Use of historical data (borrowing) from global studies is an attractive approach to meet these conflicting goals. Here, we propose a practical and relevant approach to guide the optimal borrowing rate (percent of subjects in earlier studies) and the number of subjects in the new regional bridging study. We address the limitations in global/regional exchangeability through use of a Bayesian power prior method and then optimize bridging study design with a return on investment viewpoint. The method is demonstrated using clinical data from global and Japanese trials in dapagliflozin for type 2 diabetes.

Purpose Imaging time-series data routinely collected in clinical trials are predominantly explored for covariates as covariates for survival analysis to support decision-making in oncology drug development. The key objective of this study was to assess if insights regarding two relapse resistance modes, de-novo (treatment selects out a pre-existing resistant clone) or acquired (resistant clone develops during treatment), could be inferred from such data. Methods Individual lesion size time-series data were collected from ten Phase III study arms where patients were treated with either first-generation EGFR inhibitors (erlotinib or gefitinib) or chemotherapy (paclitaxel/carboplatin combination or docetaxel). The data for each arm of each study were analysed via a competing models framework to determine which of the two mathematical models of resistance, de-novo or acquired, best-described the data. Results Within the first-line setting (treatment naive patients), we found that the de-novo model best-described the gefitinib data, whereas, for paclitaxel/carboplatin, the acquired model was preferred. In patients pre-treated with paclitaxel/carboplatin, the acquired model was again preferred for docetaxel (chemotherapy), but for patients receiving gefitinib or erlotinib, both the acquired and de-novo models described the tumour size dynamics equally well. Furthermore, in all studies where a single model was preferred, we found a degree of correlation in the dynamics of lesions within a patient, suggesting that there is a degree of homogeneity in pharmacological response. Conclusions This analysis highlights that tumour size dynamics differ between different treatments and across lines of treatment. The analysis further suggests that these differences could be a manifestation of differing resistance mechanisms. Electronic supplementary material The online version of this article (10.1007/s00280-019-03840-3) contains supplementary material, which is available to authorized users.

Olaparib is a poly ADP-ribose polymerase inhibitor that induces synthetic lethality in tumors with deficient homologous recombination repair. Population exposure-response analyses were performed to evaluate the efficacy and safety of olaparib exposure in patients with cancer. Data from multiple phase I/II/III clinical studies from both capsule and tablet formulations were combined for efficacy (N = 410) and safety (N = 757) analyses. Exposure-progression-free survival (Cox proportional hazards model indicated that a 300 mg b.i.d. tablet was statistically superior to the 200 mg b.i.d. tablet dose (hazard ratio of 0.96), although the difference was small. Exposure-safety logistic regression models and hemoglobin models predicted similar probability of safety events or hemoglobin decrease with largely overlapping 95% confidence intervals at 300 mg b.i.d. tablet, 200 mg b.i.d. tablet, and 400 mg b.i.d. capsule. The analyses provided key assessments to support the approval of olaparib 300 mg tablet therapeutic dose in patients with ovarian and breast cancer, regardless of their breast cancer (BRCA) mutation status.

As the lightest constructional metal on earth, magnesium alloys offer excellent potential for weight reduction in the transportation industry and it was observed that some magnesium alloys exhibit superior ductility and superplastic behaviour at high temperatures. The main limitation of the Superplastic forming (SPF) includes the low production rate since it needs a long forming time for each part. Through this study, an SPF process that starts with a mechanical pre-forming stage is developed to promote formability and reduce forming time. A two-dimensional finite element model is used to simulate the process. The forming process consists of two steps. At the pre-forming step (deep drawing), the sheet is drawn into the die to a preselected level, using a mechanical punch, and at the second step (SPF) a pressurized gas is applied at a controlled rate. It is shown that a significant reduction in forming time and improved final thickness uniformity can be achieved when the hybrid forming technique is used, where the process achieved a fully formed part at 400°C. Investigation for the impact of different forming process parameters achieved by comparing forming time and the distribution of final thickness that were obtained from the simulation analysis. Maximum thinning decreased from over 67% to less than 55% and forming time significantly decreased by more than 6 minutes, and the required gas pressure profile was predicted for optimum forming process parameters based on the 0.001/sec target constant strain rate within the sheet.

SummaryBackgroundAntiviral monoclonal antibodies (mAbs) developed for treatment of COVID-19 reduce the magnitude and duration of viral shedding and can thus potentially contribute to reducing transmission of the causative virus, severe acute respiratory coronavirus 2 (SARS-CoV-2). However, use of these mAbs in combination with a vaccine program has not been considered in public health strategic planning.MethodsWe developed an agent-based model to characterize SARS-CoV-2 transmission in the US population during an aggressive phase of the pandemic (October 2020 to April 2021), and simulated the effects on infections and mortality of combining mAbs as treatment and post-exposure prophylaxis (PEP) with a vaccine program plus non-pharmaceutical interventions. We also interrogated the impact of rapid diagnostic testing, increased mAb supply, and vaccine rollout.FindingsAllocation of mAbs as PEP or targeting those ≥65 years provided the greatest incremental benefits relative to vaccine in averting infections and deaths, by up to 17% and 41%, respectively. Rapid testing, facilitating earlier diagnosis and mAb use, amplified these benefits. The model was sensitive to mAb supply; doubling supply further reduced infections and mortality, by up to two-fold, relative to vaccine. mAbs continued to provide incremental benefits even as proportion of the vaccinated population increased.InterpretationUse of anti-viral mAbs as treatment and PEP in combination with a vaccination program would substantially reduce SARS-CoV-2 transmission and pandemic burden. These results may help guide resource allocation and patient management decisions for COVID-19 and can also be used to inform public health policy for current and future pandemic preparedness.FundingRegeneron Pharmaceuticals.

Dupilumab demonstrated efficacy with an acceptable safety profile in two randomized, double-blind, placebo-controlled, parallel-group, phase III trials in adolescents (12-17 years; LIBERTY AD ADOL) and children (6-11 years; LIBERTY AD PEDS) with atopic dermatitis (AD) treated for 16 weeks. Here, we present the pharmacokinetic profiles and exposure-response relationships of dupilumab that guided the posology in these populations. A total of 251 adolescent patients with moderate-to-severe AD were randomized to subcutaneous dupilumab monotherapy every 2 weeks (q2w) (200 mg q2w, baseline weight

This study is concerned with studying the performance of SiO2–water nanofluid flow through a three-dimensional straight mini-channel with different values of aspect ratio (AR) of (0.5, 1.0, and 1.6) and a fixed hydraulic diameter under a uniform heat flux. The governing equations are developed and solved numerically using the finite volume method for a single-phase flow with standard Kappa-Epsilon (ҡ–ɛ) turbulence model via a user-defined function (UDF) over the Reynolds number (Re) range of (10,000–35,000). Numerical results indicated that the average Nusselt number ratio increases as the Reynolds number and volume concentration of the nanoparticles increase for all values of the channel aspect ratio. The results indicated that the maximum enhancement of the heat transfer coefficient (benefit) achieved is 94.69% at AR = 0.5, along with the lowest increase of pressure drop (penalty) of 13.1%. The highest performance evaluation criterion (PEC) of 1.64 is found at AR = 0.5, Re = 35,000, and 5% concentration.

This chapter will focus on disseminated intravascular coagulation (DIC), a condition associated with substantial morbidity and mortality in adults and children alike. This is an intense area of research and the pathophysiology driving this condition is being understood at an ever increasing level of sophistication and detail. The underlying conditions predisposing to DIC will be described including sepsis, trauma, vascular anomalies and oncologic diseases. In addition, the clinical aspects of DIC will be considered and the differential diagnoses delineated. Knowing these differential diagnoses is vital to the pediatric intensive care practitioner as a number of these conditions have specific therapies that may improve outcomes if implemented in a timely manner. Further, the available scoring systems used in identifying overt DIC and sepsis-induced coagulopathy will be provided. Treatment options based on knowledge of DIC pathophysiology will be reviewed and the results of corresponding clinical trials assessing their impact will be described.

Inherited platelet disorders are rare but they can have considerable clinical impacts, and studies of their causes have advanced understanding of platelet formation and function. Effective hemostasis requires adequate circulating numbers of functional platelets. Quantitative, qualitative and combined platelet disorders with a bleeding phenotype have been linked to defects in platelet cytoskeletal elements, cell surface receptors, signal transduction pathways, secretory granules and other aspects. Inherited platelet disorders have variable clinical presentations, and diagnosis and management is often challenging. Evaluation begins with detailed patient and family histories, including a bleeding score. The physical exam identifies potential syndromic features of inherited platelet disorders and rules out other causes. Laboratory investigations include a complete blood count, blood film, coagulation testing and Von Willebrand factor assessment. A suspected platelet function disorder is further assessed by platelet aggregation, flow cytometry, platelet dense granule release and/or content, and genetic testing. The management of platelet function disorders aims to minimize the risk of bleeding and achieve adequate hemostasis when needed. Although not universal, platelet transfusion remains a crucial component in the management of many inherited platelet disorders.

Objectives The term discrepant hemophilia A (DHA) denotes the discrepancy between factor VIII activity (FVIII:C) measured by different assay methodologies in patients with nonsevere hemophilia A (HA). The objective was to review the characteristics and the current understanding of mechanisms contributing to assay discrepancy in DHA. Methods Characteristics of the DHA patients treated were examined by retrospective chart review. In addition, a literature review was performed to determine the current understanding of DHA. Results Three cases of DHA were diagnosed based on bleeding phenotype: 2 cases represented missed diagnoses of HA, and 1 represented misclassification of hemophilia severity. The revised diagnosis and classification of hemophilia directly affected clinical management. Review of the literature identified 18 articles with an estimated pooled prevalence of 36% (95% CI, 23%-56%; I2 = 85%; P Conclusions Our experience and literature review suggested that DHA is not only a laboratory phenomenon—it can affect clinical management in a subset of patients. A high index of suspicion for DHA is necessary while evaluating bleeding patients and/or classifying nonsevere HA.

A palladium(II) catalyst, in the presence of Selectfluor, enables the efficient and chemoselective transformation of primary amides into nitriles. The amides can be attached to aromatic rings, heteroaromatic rings, or aliphatic side chains, and the reactions tolerate steric bulk and electronic modification. Dehydration of a peptaibol containing three glutamine groups afforded structure–activity relationships for each glutamine residue. Thus, this dehydration can act similarly to an alanine scan for glutamines via synthetic mutation.

Selumetinib (AZD6244, ARRAY-142886) is a mitogen-activated protein kinase kinase inhibitor that has been tested for treatment of non-small cell lung cancer (NSCLC). Selumetinib (75 mg twice daily) plus docetaxel in patients with advanced NSCLC has been assessed in phase 2 (SELECT-2) and phase 3 (SELECT-1) clinical trials. The objective of the current analysis was to investigate the exposure-response relationship of selumetinib in these 2 clinical trials, based on the development of a population pharmacokinetic (PopPK) model for selumetinib and its active metabolite, N-desmethyl selumetinib, in patients with NSCLC. A PopPK model using data from seven phase 1 studies was first developed and served as prior information for the development of the patient PopPK model. The pharmacokinetics (PK) of selumetinib and N-desmethyl selumetinib were modeled simultaneously. A two-compartment model with zero-first order absorption and first-order elimination reasonably described the selumetinib PK. The N-desmethyl metabolite of selumetinib was described by a one-compartment model with first-order elimination. The final PK parameter estimates were similar between patients with NSCLC and patients in the phase 1 population. Selumetinib apparent clearance and central volume of distribution were 11.9 L/h and 32.1 L, respectively, in patients. Individual selumetinib exposure metrics were estimated to investigate the correlation between exposure and efficacy/safety endpoints observed in NSCLC studies. There was no significant difference in progression-free survival (the primary endpoint) among the different quartiles of exposure. Similarly, no significant correlation was observed between selumetinib exposure and other secondary efficacy or safety endpoints. The conclusions are in accordance with the reported clinical findings.

ATM inhibitors, such as 7, have demonstrated the antitumor potential of ATM inhibition when combined with DNA double-strand break-inducing agents in mouse xenograft models. However, the properties of 7 result in a relatively high predicted clinically efficacious dose. In an attempt to minimize attrition during clinical development, we sought to identify ATM inhibitors with a low predicted clinical dose (50 mg) and focused on strategies to increase both ATM potency and predicted human pharmacokinetic half-life (predominantly through the increase of volume of distribution). These efforts resulted in the discovery of 64 (AZD0156), an exceptionally potent and selective inhibitor of ATM based on an imidazo[4,5- c]quinolin-2-one core. 64 has good preclinical phamacokinetics, a low predicted clinical dose, and a high maximum absorbable dose. 64 has been shown to potentiate the efficacy of the approved drugs irinotecan and olaparib in disease relevant mouse models and is currently undergoing clinical evaluation with these agents.

Modeling the relationship between drug concentrations and heart rate corrected QT interval (QTc) change from baseline (C-∆QTc), based on Phase I single ascending dose (SAD) or multiple ascending dose (MAD) studies, has been proposed as an alternative to thorough QT studies (TQT), in assessing drug-induced QT prolongation risk. The present analysis used clinical SAD, MAD and TQT study data of an experimental compound, AZD5672, to evaluate the performance of: (i) three computational platforms (linear mixed-effects modeling implemented via PROC MIXED in SAS, as well as in R using LME4 package and linear quantile mixed models (LQMM) implemented via LQMM package; (ii) different model structures with and without treatment- or time-specific intercepts; and (iii) three methods for calculating the confidence interval (CI) of QTc prolongation (analytical and bootstrap methods with fixed or varied geometric mean concentrations). We show that treatment- and time-specific intercepts may need to be included into C-∆QTc modeling through PROC MIXED or LME4, regardless of their statistical significance. With the intersection union test (IUT) in the TQT study as a reference for comparison, inclusion of these intercepts increased the feasibility for C-∆QTc modelling of SAD or MAD to reach the same conclusion as the IUT analysis based on TQT study. Compared to PROC MIXED or LME4, the LQMM method is less dependent on inclusion of treatment- or time-specific intercepts, and the bootstrap CI calculation methods provided higher likelihood for C-∆QTc modeling of SAD and MAD studies to reach the same conclusion as the IUT based on the TQT study.

Background Numerous oncology combination therapies involving modulators of the cancer immune cycle are being developed, yet quantitative simulation models predictive of outcome are lacking. We here present a model-based analysis of tumor size dynamics and immune markers, which integrates experimental data from multiple studies and provides a validated simulation framework predictive of biomarkers and anti-tumor response rates, for untested dosing sequences and schedules of combined radiation (RT) and anti PD-(L)1 therapies. Methods A quantitative systems pharmacology model, which includes key elements of the cancer immunity cycle and the tumor microenvironment, tumor growth, as well as dose-exposure-target modulation features, was developed to reproduce experimental data of CT26 tumor size dynamics upon administration of RT and/or a pharmacological IO treatment such as an anti-PD-L1 agent. Variability in individual tumor size dynamics was taken into account using a mixed-effects model at the level of tumor-infiltrating T cell influx. Results The model allowed for a detailed quantitative understanding of the synergistic kinetic effects underlying immune cell interactions as linked to tumor size modulation, under these treatments. The model showed that the ability of T cells to infiltrate tumor tissue is a primary determinant of variability in individual tumor size dynamics and tumor response. The model was further used as an in silico evaluation tool to quantitatively predict, prospectively, untested treatment combination schedules and sequences. We demonstrate that anti-PD-L1 administration prior to, or concurrently with RT reveal further synergistic effects, which, according to the model, may materialize due to more favorable dynamics between RT-induced immuno-modulation and reduced immuno-suppression of T cells through anti-PD-L1. Conclusions This study provides quantitative mechanistic explanations of the links between RT and anti-tumor immune responses, and describes how optimized combinations and schedules of immunomodulation and radiation may tip the immune balance in favor of the host, sufficiently to lead to tumor shrinkage or rejection. Electronic supplementary material The online version of this article (10.1186/s40425-018-0327-9) contains supplementary material, which is available to authorized users.

Aims A multistudy analysis of cediranib, a potent, selective inhibitor of all three vascular endothelial growth factor receptors (VEGFR-1, -2 and -3), was conducted to establish population exposure-safety models for the relationship of cediranib exposure to the safety endpoints, diastolic and systolic blood pressure (DBP and SBP) and diarrhoea in cancer patients. These models were applied to predict safety outcomes for different cediranib dose regimens. Methods Models for hypertension and diarrhoea were constructed based on data from 10 Phase I and three Phase II studies comprising 631 cancer patients following cediranib once-daily oral dosing. Daily DBP and SBP were simultaneously characterized using indirect response models for predicted cediranib concentration-time courses, while daily diarrhoea events were modelled as ordered categorical variables with a proportional odds model with a Markov element for predicted average cediranib concentrations. Results For 20 mg cediranib once-daily oral administration, the mean increase in DBP and SBP was predicted to be 7 (95% CI 3-13) and 8 mmHg (95% CI 3-16), respectively, while the probability of mild diarrhoea, but not the severity, was predicted to increase over time. Severe diarrhoea was predicted to be resolved rapidly upon discontinuation of cediranib treatment. Conclusions Maximum blood pressure increase was observed within the first few days of cediranib treatment, consistent with the pharmacokinetic profile of cediranib reaching steady state in about 5 days. The probability of diarrhoea increased with cediranib concentration but was far more dependent on the status of diarrhoea predicted on the previous day.

Quantitative pharmacology (QP) applications in translational medicine, drug-development, and therapeutic use were crowd-sourced by the ASCPT Impact and Influence initiative. Highlighted QP case studies demonstrated faster access to innovative therapies for patients through 1) rational dose selection for pivotal trials; 2) reduced trial-burden for vulnerable populations; or 3) simplified posology. Critical success factors were proactive stakeholder engagement, alignment on the value of model-informed approaches, and utilizing foundational clinical pharmacology understanding of the therapy.