Pembrolizumab is approved globally at a dose of 200 mg every 3 weeks (Q3W) or 400 mg every 6 weeks (Q6W) intravenously (IV). These dosing recommendations are based on established regimens that have demonstrated efficacy in clinical trials. Recently, pembrolizumab dosing at 4 mg/kg Q6W has been suggested as an alternative regimen; however, efficacy has not been evaluated in any prospective, controlled clinical trial. The objective was to describe the pharmacokinetic model-based analyses of pembrolizumab 4 mg/kg Q6W IV compared with approved dosing regimens. The pharmacokinetic profiles for pembrolizumab were simulated for 4 mg/kg Q6W, 400 mg Q6W, 200 mg Q3W, and 2 mg/kg Q3W IV in 3607 participants from clinical trials of pembrolizumab across tumor types and were based on an established pharmacokinetic model informed by extensive clinical data that supported the approved pembrolizumab IV doses. Pharmacokinetic exposure measures evaluated were trough concentration (Ctrough) and area under the curve (AUC) after initial dosing (first 6 weeks of treatment) and at steady state (weeks 13–18). Pembrolizumab 4 mg/kg Q6W IV resulted in Ctrough levels consistently below the lowest clinically evaluated thresholds associated with the approved fixed dose of 400 mg Q6W and weight-based dose of 2 mg/kg Q3W and well below those of 200 mg Q3W, which is the gold-standard dose with the most extensive pan tumor clinical data. In the overall population, the geometric mean steady state Ctrough for 4 mg/kg Q6W was 26

Oncolytic viruses (OVs) are a growing immuno-oncology therapeutic class that rely on their capability to activate the dormant endogenous anti-tumor immune response in order to control or eradicate tumor cells. Given their intrinsic mechanisms of action and their biological nature, development of antidrug antibodies (ADA) represents an important aspect to consider during clinical evaluation. ADAs can potentially affect viral kinetics and/or dynamics, ultimately resulting in reductions or even loss of drug efficacy. Here, we present a semi-mechanistic pharmacokinetic/pharmacodynamic model characterizing the interplay between V937 and neutralizing ADA in cancer patients receiving the V937 oncolytic virus. The quantitative framework has been developed integrating viral load and ADA titers from 208 cancer patients who received V937 following intratumoral or intravascular administration, in monotherapy or in combination with pembrolizumab. The model successfully captured both V937 time course and the dynamics of ADAs under the different settings, showing no meaningful impact of ADAs on viral kinetics. Moreover, tumor response was neither affected by the preexistence or development of ADAs, which can be explained by the primary role of the immune system in the response. This quantitative and (semi-) mechanistic framework can be expanded to other oncolytic viruses and used to explore under which scenarios a relevant impact could be observed, thus supporting the development of novel oncolytic viral therapies.

Immuno-oncology (IO) is a growing strategy in cancer treatment. Oncolytic viruses (OVs) can selectively infect cancer cells and lead to direct and/or immune-dependent tumor lysis. This approach represents an opportunity to potentiate the efficacy of immune checkpoint inhibitors (ICI), such as pembrolizumab. Currently, there is a lack of comprehensive quantitative models for the aforementioned scenarios. In this work, we developed a mechanistic framework describing viral kinetics, viral dynamics, and tumor response after intratumoral (i.t.) or intravenous (i.v.) administration of V937 alone or in combination with pembrolizumab. The model accounts for tumor shrinkage, in both injected and non-injected lesions, induced by: viral-infected tumor cell death and activated CD8 cells. OV-infected tumor cells enhanced the expansion of CD8 cells, whereas pembrolizumab inhibits their exhaustion by competing with PD-L1 in their binding to PD-1. Circulating viral levels and treatment effects on tumor volume were adequately characterized in all the different scenarios. This mechanistic-based model has been developed by combining top-down and bottom-up approaches and provides individual estimates of viral and ICI responses. The robustness of the model is reflected by the description of the tumor size time profiles in a variety of clinical scenarios. Additionally, this platform allows us to investigate not only the contribution of processes related to the viral kinetics and dynamics on tumor response, but also the influence of its interaction with an ICI. Additionally, the model can be used to explore different scenarios aiming to optimize treatment combinations and support clinical development.

Selumetinib is clinically used for pediatric patients with neurofibromatosis type 1 and symptomatic, inoperable plexiform neurofibromas. Until recently, selumetinib had to be taken twice daily, after 2 hours of fasting and followed by 1 hour of fasting, which could be inconvenient. This population analysis evaluated the effect of low- and high-fat meals on the pharmacokinetic (PK) parameters of selumetinib and its active metabolite N-desmethyl selumetinib. The dataset comprised 511 subjects from 15 clinical trials who received ≥1 dose of selumetinib and provided ≥1 measurable postdose concentration of selumetinib and N-desmethyl selumetinib. A 2-compartment model with sequential 0- and 1st-order delayed absorption and 1st-order elimination adequately described selumetinib PK characteristics. A 1-compartment model reasonably described N-desmethyl selumetinib PK characteristics over time simultaneously with selumetinib. Selumetinib geometric mean area under the concentration-time curve ratio (1-sided 90% confidence interval [CI] lower bound) was 76.9% (73.3%) with a low-fat meal and 79.3% (76.3%) with a high-fat meal versus fasting. The lower bound of the 1-sided 90% CI demonstrated a difference of <30% between fed and fasted states. Considering the flat exposure-response relationship within the dose range (20-30 mg/m2), the observed range of exposure, and the variability in the SPRINT trial, this was not considered clinically relevant.

SummaryMEK inhibitors have immunomodulatory activity and potential for synergistic activity when combined with PD-1 inhibitors. We evaluated selumetinib (inhibitor of MEK1/2) plus pembrolizumab (anti‒PD-1 antibody) in patients with advanced/metastatic solid tumors. In this phase 1b study, adults with previously treated advanced/metastatic solid tumors received pembrolizumab 200 mg intravenously every 3 weeks plus selumetinib on days 1‒14 per 3-week cycle (2 weeks on/1 week off); selumetinib dosing began at 50 mg orally twice daily with escalation in 25 mg increments for ≤ 35 cycles. Primary endpoints were dose-limiting toxicities (DLTs), adverse events (AEs), and treatment discontinuations due to AEs. Thirty-two patients were enrolled. Dose escalation was completed up to selumetinib 125 mg twice daily. The target DLT rate of 30% was not reached at any dose level. In the selumetinib 100 mg group, 2/11 patients (18.2%) experienced DLTs (n = 1 grade 3 diarrhea, n = 1 grade 3 fatigue). In the selumetinib 125 mg group, 3/14 (21.4%) experienced DLTs (n = 1 grade 2 retinal detachment, n = 1 grade 3 retinopathy, n = 1 grade 3 stomatitis). Dose-related changes in pharmacokinetic exposures were observed for selumetinib and N-desmethyl selumetinib up to 100 mg (saturation at 125 mg). Two patients achieved partial responses (1 each with selumetinib 75 mg and 125 mg) for an objective response rate of 6%. The study was stopped early because of insufficient efficacy. Although the target DLT rate was not reached at any dose level and no new safety signals were identified, selumetinib plus pembrolizumab had limited antitumor activity in this population. Trial registration: ClinicalTrials.gov, NCT03833427.

C-X-C motif chemokine receptor 2 (CXCR2) has a role in tumor progression, lineage plasticity, and reduction of immune checkpoint inhibitor efficacy. Preclinical evidence suggests potential benefit of CXCR2 inhibition in multiple solid tumors. In this phase 2 study (NCT03473925), adults with previously treated advanced or metastatic castration-resistant prostate cancer (CRPC), microsatellite-stable colorectal cancer (MSS CRC), or non-small-cell lung cancer (NSCLC) were randomized 1:1 to the CXCR2 antagonist navarixin 30 or 100 mg orally once daily plus pembrolizumab 200 mg intravenously every 3 weeks up to 35 cycles. Primary endpoints were investigator-assessed objective response rate (RECIST v1.1) and safety. Of 105 patients (CRPC, n=40; MSS CRC, n=40; NSCLC, n=25), 3 had a partial response (2 CRPC, 1 MSS CRC) for ORRs of 5%, 2.5%, and 0%, respectively. Median progression-free survival was 1.8-2.4 months without evidence of a dose-response relationship, and the study was closed at a prespecified interim analysis for lack of efficacy. Dose-limiting toxicities occurred in 2/48 patients (4%) receiving navarixin 30 mg and 3/48 (6%) receiving navarixin 100 mg; events included grade 4 neutropenia and grade 3 transaminase elevation, hepatitis, and pneumonitis. Treatment-related adverse events occurred in 70/105 patients (67%) and led to treatment discontinuation in 7/105 (7%). Maximal reductions from baseline in absolute neutrophil count were 44.5%-48.2% (cycle 1) and 37.5%-44.2% (cycle 2) and occurred within 6-12 hours postdose in both groups. Navarixin plus pembrolizumab did not demonstrate sufficient efficacy in this study. Safety and tolerability of the combination were manageable. (Trial registration: ClinicalTrials.gov , NCT03473925).

Tissue clearing and Light sheet fluorescence microscopy (LSFM) provide spatial information at a subcellular resolution in intact organs and tumors which is a significant advance over tools that limit imaging to a few representative tissue sections. The spatial distribution of drugs, targets, and biomarkers can help inform relationships between exposure at the site of action, efficacy, and safety during drug discovery. We demonstrate the use of LSFM to investigate distribution of an oncolytic virus (OV) and vasculature in xenograft tumors, as well as brain Aβ pathology in an Alzheimer’s disease (AD) mouse model. Machine learning-based image analysis tools developed to segment vasculature in tumors showed that random forest and deep learning methods provided superior segmentation accuracy vs intensity-based thresholding. Sub-cellular resolution enabled detection of punctate and diffuse intracellular OV distribution profiles. LSFM investigation in the brain in a TgCRND8 AD mouse model at 6.5 months of age enabled evaluation of Aβ plaque density in different brain regions. The utility of LSFM data to support quantitative systems pharmacology (QSP) and physiology-based pharmacokinetics (PBPK) modeling to inform drug development are also discussed. In summary, we showcase how LSFM can expand our understanding of macromolecular drug and biomarker distribution to advance drug discovery and development.

Aim: We evaluated MK-8353 (small molecule inhibitor of extracellular signal-regulated kinase 1/2) plus selumetinib (mitogen-activated extracellular signal-regulated kinase 1/2 inhibitor) in patients with advanced solid tumors. Methods: This phase 1b, open-label, dose-escalation study (NCT03745989) enrolled adults with histologically/cytologically documented, locally advanced/metastatic solid tumors. MK-8353/selumetinib dose combinations were intended to be investigated in sequence: 50/25, 100/50, 150/75, 200/75, 200/100, and 250/100. Each agent was administered orally BID 4 days on/3 days off in repeating cycles every 21 days. Primary objectives were safety and tolerability and to establish preliminary recommended phase 2 doses for combination therapy. Results: Thirty patients were enrolled. Median (range) age was 61.5 (26−78) years and 93% had received previous cancer therapy. Among 28 patients in the dose-limiting toxicities [DLT]-evaluable population, 8 experienced DLTs: 1/11 (9%) in the MK-8353/selumetinib 100/50-mg dose level experienced a grade 3 DLT (urticaria), and 7/14 (50%) in the 150/75-mg dose level experienced grade 2/3 DLTs (n = 2 each of blurred vision, retinal detachment, vomiting; n = 1 each of diarrhea, macular edema, nausea, retinopathy). The DLT rate in the latter dose level exceeded the prespecified target DLT rate (~30%). Twenty-six patients (87%) experienced treatment-related adverse events (grade 3, 30%; no grade 4/5), most commonly diarrhea (67%), nausea (37%), and acneiform dermatitis (33%). Three patients (10%) experienced treatment-related adverse events leading to treatment discontinuation. Best response was stable disease in 14 patients (n = 10 with MK-8353/selumetinib 150/75 mg). Conclusion: MK-8353/selumetinib 50/25 mg and 100/50 mg had acceptable safety and tolerability, whereas 150/75 mg was not tolerable. No responses were observed.

Introduction: Oncolytic viruses (OVs) represent a novel therapeutic strategy in oncology due to their capability to selectively infect and replicate in cancer cells, triggering a direct and/or immune-induced tumor lysis. However, the mechanisms governing OV pharmacokinetics are still poorly understood. This work aims to develop a physiologically based pharmacokinetic model of the novel OV, V937, in non-tumor-bearing mice to get a quantitative understanding of its elimination and tissue uptake processes. Materials and methods: Model development was performed using data obtained from 60 mice. Viral levels were quantified from eight tissues after a single intravenous V937 dose. An external dataset was used for model validation. This test set included multiple-dose experiments with different routes of administration. V937 distribution in each organ was described using a physiological structure based on mouse-specific organ blood flows and volumes. Analyses were performed using the non-linear mixed-effects approach with NONMEM 7.4. Results: Viral levels showed a drop from 10 8 to 10 5 copies/µg RNA at day 1 in blood, reflected in a high estimate of total clearance (18.2 mL/h). A well-stirred model provided an adequate description for all organs except the muscle and heart, where a saturable uptake process improved data description. The highest numbers of viral copies were observed in the brain, lymph node, kidney, liver, lung, and spleen on the first day after injection. On the other hand, the maximum amount of viral copies in the heart, muscle, and pancreas occurred 3 days after administration. Conclusion: To the best of our knowledge, this is the first physiologically based pharmacokinetic model developed to characterize OV biodistribution, representing a relevant source of quantitative knowledge regarding the in vivo behavior of OVs. This model can be further expanded by adding a tumor compartment, where OVs could replicate.

Oncolytic viruses (OVs) represent a potential therapeutic strategy in cancer treatment. However, there is currently a lack of comprehensive quantitative models characterizing clinical OV kinetics and distribution to the tumor. In this work, we present a mechanistic modeling framework for V937 OV, after intratumoral (i.t.) or intravascular (i.v.) administration in patients with cancer. A minimal physiologically-based pharmacokinetic model was built to characterize biodistribution of OVs in humans. Viral dynamics was incorporated at the i.t. cellular level and linked to tumor response, enabling the characterization of a direct OV killing triggered by the death of infected tumor cells and an indirect killing induced by the immune response. The model provided an adequate description of changes in V937 mRNA levels and tumor size obtained from phase I/II clinical trials after V937 administration. The model showed prominent role of viral clearance from systemic circulation and infectivity in addition to known tumor aggressiveness on clinical response. After i.v. administration, i.t. exposure of V937 was predicted to be several orders of magnitude lower compared with i.t. administration. These differences could be overcome if there is high virus infectivity and/or replication. Unfortunately, the latter process could not be identified at the current clinical setting. This work provides insights on selecting optimal OV considering replication rate and infectivity.

Supplementary material and tables

Journal Article High-Resolution Ex Vivo Tissue Clearing, Lightsheet Imaging, and Data Analysis to Support Macromolecular Drug and Biomarker Distribution in Whole Organs and Tumors Get access Niyanta Kumar, Niyanta Kumar ADME & Discovery Toxicology, Merck & Co. Inc., West Point, PA, United States Corresponding author: niyanta.kumar@merck.com Search for other works by this author on: Oxford Academic Google Scholar Petr Hrobař, Petr Hrobař Data Science & Scientific Informatics, MSD, Prague, Czech Republic Search for other works by this author on: Oxford Academic Google Scholar Martin Vagenknecht, Martin Vagenknecht Data Science & Scientific Informatics, MSD, Prague, Czech Republic Search for other works by this author on: Oxford Academic Google Scholar Jindrich Soukup, Jindrich Soukup Data Science & Scientific Informatics, MSD, Prague, Czech Republic Search for other works by this author on: Oxford Academic Google Scholar Peter Bloomingdale, Peter Bloomingdale Quantitative Pharmacology and Pharmacometrics, Merck & Co. Inc., Boston, MA, United States Search for other works by this author on: Oxford Academic Google Scholar Tomoko Freshwater, Tomoko Freshwater Quantitative Pharmacology and Pharmacometrics, Merck & Co. Inc., Rahway, NJ, United States Search for other works by this author on: Oxford Academic Google Scholar Sophia Bardehle, Sophia Bardehle Neuroscience, Merck & Co. Inc., Boston, MA, United States Search for other works by this author on: Oxford Academic Google Scholar Roman Peter, Roman Peter Data Science & Scientific Informatics, MSD, Prague, Czech Republic Search for other works by this author on: Oxford Academic Google Scholar Nadia Patterson, Nadia Patterson ADME & Discovery Toxicology, Merck & Co. Inc., West Point, PA, United States Search for other works by this author on: Oxford Academic Google Scholar Ruban Mangadu, Ruban Mangadu Immuno-Oncology, Merck & Co. Inc., San Francisco, CA, United States Search for other works by this author on: Oxford Academic Google Scholar ... Show more Cinthia Pastuskovas, Cinthia Pastuskovas ADME & Discovery Toxicology, Merck & Co. Inc., San Francisco, CA, United States Search for other works by this author on: Oxford Academic Google Scholar Mark Cancilla Mark Cancilla ADME & Discovery Toxicology, Merck & Co. Inc., West Point, PA, United States Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 28, Issue S1, 1 August 2022, Pages 1436–1437, https://doi.org/10.1017/S1431927622005840 Published: 01 August 2022

Despite numerous publications emphasizing the value of dose finding, drug development in oncology is dominated by the mindset that higher dose provides higher efficacy. Examples of dose finding implemented by biopharmaceutical firms can change this mindset. The purpose of this article is to outline a pragmatic dose selection strategy for immuno‐oncology (IO) and other targeted monoclonal antibodies (mAbs). The approach was implemented for pembrolizumab. Selecting a recommended phase II dose (RP2D) with a novel mechanism of action is often challenging due to uncertain relationships between pharmacodynamics measurements and clinical end points. Additionally, phase I efficacy and safety data are generally inadequate for RP2D selection for IO mAbs. Here, the RP2D was estimated based on phase I (clinical study KN001 A and A2) pharmacokinetics data as the dose required for target saturation, which represents a surrogate for maximal pharmacological effect for antagonist mAbs. Due to limitations associated with collecting and analyzing tumor biopsies, characterizing intratumoral target engagement (TE) is challenging. To overcome this gap, a physiologically‐based pharmacokinetic model was implemented to predict intratumoral TE. As tumors are spatially heterogeneous, TE was predicted in well‐vascularized and poorly vascularized tumor regions. Additionally, impact of differences in target expression, for example, due to interindividual variability and cancer type, was simulated. Simulations showed that 200 mg every 3 weeks can achieve ≥ 90% TE in clinically relevant scenarios, resulting in the recommendation of 200 mg every 3 weeks as the RP2D. Randomized dose comparison studies (KN001 B2 and D) showing similar efficacy over a fivefold dose/exposure range confirmed the RP2D as the pivotal dose.

Selumetinib (ARRY-142886) is a potent, selective, MEK1/2 inhibitor approved in the US for the treatment of children (≥ 2 years) with neurofibromatosis type 1 (NF1) and symptomatic, inoperable plexiform neurofibromas (PN). We characterized population pharmacokinetics (PK) of selumetinib and its active N‐desmethyl metabolite, evaluated exposure–safety/efficacy relationships, and assessed the proposed therapeutic dose of 25 mg/m2 bid based on body surface area (BSA) in this patient population. Population PK modeling and covariate analysis (demographics, formulation, liver enzymes, BSA, patients/healthy volunteers) were based on pooled PK data from adult healthy volunteers (n = 391), adult oncology patients (n = 83) and pediatric patients with NF1-PN (n = 68). Longitudinal selumetinib/metabolite exposures were predicted with the final model. Exposure–safety/efficacy analyses were applied to pediatric patients (dose levels: 20, 25, 30 mg/m2 bid). Selumetinib and metabolite concentration–time courses were modeled using a joint compartmental model. Typical selumetinib plasma clearance was 11.6 L/h (95% CI 11.0–12.2 L/ h). Only BSA had a clinically relevant (> 20%) impact on exposure, supporting BSA-based administration in children. Selumetinib and metabolite exposures in responders (≥ 20% PN volume decrease from baseline) and non-responders were largely overlapping, with medians numerically higher in responders. No clear relationships between exposure and safety events were established; exposure was not associated with key adverse events (AEs) including rash acneiform, diarrhea, vomiting, and nausea. Findings support continuous selumetinib 25 mg/m2 bid in pediatric patients. Importantly, the updated dosing nomogram ensures that patients will receive a clinically active, yet tolerable, dose regardless of differences in BSA and allows dose reductions, if necessary.

Selumetinib (ARRY‐142886), an oral, potent and highly selective allosteric mitogen‐activated protein kinase kinase 1/2 inhibitor, is approved by the US Food and Drug Administration for the treatment of pediatric patients aged ≥2 years with neurofibromatosis type 1 with symptomatic, inoperable plexiform neurofibromas. A physiologically based pharmacokinetic (PBPK) model was constructed to predict plasma concentration–time profiles of selumetinib, and to evaluate the impact of coadministering moderate cytochrome P450 (CYP) 3A4/2C19 inhibitors/inducers. The model was also used to extrapolate pharmacokinetic exposures from older children with different body surface area to guide dosing in younger children. This model was built based on physiochemical data and clinical in vivo drug‐drug interaction (DDI) studies with itraconazole and fluconazole, and verified against data from an in vivo rifampicin DDI study and an absolute bioavailability study. The pediatric model was updated by changing system‐specific input parameters using the Simcyp pediatric module. The model captured the observed selumetinib pharmacokinetic profiles and the interactions with CYP inhibitors/inducers. The predictions from the PBPK model showed a DDI effect of 30% to 40% increase or decrease in selumetinib exposure when coadministered with moderate CYP inhibitors or inducers, respectively, which was used to inform dose management and adjustments. The pediatric PBPK model was applied to simulate exposures in specific body surface area brackets that matched those achieved with a 25 mg/m 2 dose in SPRINT clinical trials. The pediatric PBPK model was used to guide the dose for younger patients in a planned pediatric clinical study.

V937 is an investigational novel oncolytic non-genetically modified Kuykendall strain of Coxsackievirus A21 which is in clinical development for the treatment of advanced solid tumor malignancies. V937 infects and lyses tumor cells expressing the intercellular adhesion molecule I (ICAM-I) receptor. We integrated in vitro and in vivo data from six different preclinical studies to build a mechanistic model that allowed a quantitative analysis of the biological processes of V937 viral kinetics and dynamics, viral distribution to tumor, and anti-tumor response elicited by V937 in human xenograft models in immunodeficient mice following intratumoral and intravenous administration. Estimates of viral infection and replication which were calculated from in vitro experiments were successfully used to describe the tumor response in vivo under various experimental conditions. Despite the predicted high clearance rate of V937 in systemic circulation (t(1/2) = 4.3 min), high viral replication was observed in immunodeficient mice which resulted in tumor shrinkage with both intratumoral and intravenous administration. The described framework represents a step towards the quantitative characterization of viral distribution, replication, and oncolytic effect of a novel oncolytic virus following intratumoral and intravenous administrations in the absence of an immune response. This model may further be expanded to integrate the role of the immune system on viral and tumor dynamics to support the clinical development of oncolytic viruses.

AbstractPurpose: Preclinical studies show that adavosertib, a WEE1 kinase inhibitor, sensitizes TP53-mutant cells to chemotherapy. We hypothesized that adavosertib, plus chemotherapy, would enhance efficacy versus placebo in TP53-mutated ovarian cancer. Patients and Methods: Following safety run-in, this double-blind phase II trial (NCT01357161) randomized women with TP53-mutated, platinum-sensitive ovarian cancer to oral adavosertib (225 mg twice daily for 2.5 days/21-day cycle) or placebo, plus carboplatin (AUC5) and paclitaxel (175 mg/m2), until disease progression or for six cycles. The primary endpoints were progression-free survival (PFS) by enhanced RECIST v1.1 [ePFS (volumetric)] and safety. Secondary/exploratory objectives included PFS by RECIST v1.1 (single dimension), objective response rate, overall survival, and analysis of tumor gene profile versus sensitivity to adavosertib. Results: A total of 121 patients were randomized to adavosertib (A+C; n = 59) and placebo (P+C; n = 62) plus chemotherapy. Adding adavosertib to chemotherapy improved ePFS [median, 7.9 (95% confidence interval (CI), 6.9–9.9) vs. 7.3 months (5.6–8.2); HR 0.63 (95% CI, 0.38–1.06); two-sided P = 0.080], meeting the predefined significance threshold (P < 0.2). Clinical benefit was observed following A+C for patients with different TP53 mutation subtypes, identifying possible response biomarkers. An increase in adverse events was seen with A+C versus P+C: greatest for diarrhea (adavosertib 75%; placebo 37%), vomiting (63%; 27%), anemia (53%; 32%), and all grade ≥3 adverse events (78%; 65%). Conclusions: Establishing an optimal strategy for managing tolerability and identifying specific patient populations most likely to benefit from treatment may increase clinical benefit. Future studies should consider additional adavosertib doses within the chemotherapy treatment cycle and the potential for maintenance therapy.

Objective: The purpose of this systematic literature review (SLR) and meta-analysis was to compile the response of historic treatment options in first-line settings for patient populations who are cisplatin ineligible. Materials and Methods: SLR was conducted to compile objective response rate (ORR), duration of response (DOR), progression-free survival (PFS), and overall survival (OS) of historic therapies for this population based on stringent criteria. Clinical trials published in English from January 1991 to June 2016 were identified by searching the PubMed (Medline), Cochrane, and Embase databases. Results: Eighteen studies (21 arms; N=810) were identified and used for this meta-analysis. For all treatments included in these studies, the pooled ORR was 0.36 (95% confidence interval [CI], 0.30-0.42). The ORR for the carboplatin+gemcitabine arms (6 arms; N=259), which is the National Comprehensive Cancer Network’s recommended first-line treatment (before approval of atezolizumab and pembrolizumab) for this population was 0.36 (95% CI, 0.30-0.42), the median DOR (4 arms) was 7.00 months (95% CI, 4.34-11.29), and the median OS was 8.39 months (95% CI, 7.05-9.98). Conclusions: The results of this SLR clearly demonstrate the paucity of clinical studies that assess therapeutic intervention in truly cisplatin-ineligible advanced/metastatic urothelial carcinoma subjects and highlight the development of novel therapies that can create real improvement in long-term outcomes. The recent approval of 2 checkpoint inhibitors, atezolizumab and pembrolizumab, were added in the National Comprehensive Cancer Network guidance as recommended first-line treatment for cisplatin-ineligible patients with advanced/metastatic urothelial carcinoma and has provided alternatives for this patient population.