FDA Approval Summary: Repotrectinib for Locally Advanced or Metastatic ROS1-Positive Non-Small Cell Lung Cancer.

On November 15, 2023, the U.S. Food and Drug Administration (FDA) granted traditional approval to repotrectinib (Augtyro, Bristol Myers Squibb Corporation) for the treatment of adult patients with locally advanced or metastatic receptor tyrosine kinase encoded by the ROS1 gene (ROS1)-positive non-small cell lung cancer (NSCLC). The approval was based on TRIDENT-1, a single-arm trial with multiple cohorts of patients with ROS1 fusion-positive (hereafter "ROS1-positive") NSCLC (NCT03093116), who were either treatment naïve or had received prior ROS1 tyrosine kinase inhibitor (TKI) and/or platinum-based chemotherapy. The primary efficacy outcome measure is objective response rate (ORR) assessed by blinded independent central review (BICR) using response evaluation criteria in solid tumors version 1.1. ORR was assessed in 71 patients who were ROS1 TKI naïve and 56 patients who had received a prior ROS1 TKI. Among the 71 patients who were ROS1 TKI naïve, the ORR was 79% (95% CI, 68-88), median duration of response was 34.1 months (95% CI, 26-NE). In patients who had received a prior ROS1 TKI and no prior chemotherapy, the ORR was 38% (95% CI, 25-52). The median duration of response was 14.8 months (95% CI, 7.6-NE); BICR-assessed responses were observed in CNS metastases in patients in both cohorts and in patients who developed resistance mutations following prior TKI therapy. The most common (>20%) adverse reactions were dizziness, dysgeusia, peripheral neuropathy, constipation, dyspnea, ataxia, fatigue, cognitive disorders, and muscular weakness. A unique feature of this ROS1 TKI approval is the inclusion of robust evidence of efficacy in patients with ROS1-positive NSCLC who had progressed on prior ROS1 TKIs.

FDA Approval Summary: Nivolumab Plus Ipilimumab for the Treatment of Patients with Hepatocellular Carcinoma Previously Treated with Sorafenib.

On March 10, 2020, the U.S. Food and Drug Administration (FDA) granted accelerated approval to nivolumab in combination with ipilimumab for the treatment of patients with hepatocellular carcinoma (HCC) previously treated with sorafenib. The recommended approved dosage was nivolumab 1 mg/kg i.v. plus ipilimumab 3 mg/kg i.v. every 3 weeks for four cycles, followed by nivolumab 240 mg i.v. every 2 weeks. The approval was based on data from cohort 4 of CheckMate 040, which randomized patients with advanced unresectable or metastatic HCC previously treated with or who were intolerant to sorafenib to receive one of three different dosing regimens of nivolumab in combination with ipilimumab. Investigator-assessed overall response rate (ORR) was the primary endpoint, and ORR assessed by blinded independent central review (BICR) was an exploratory endpoint. BICR-assessed ORR and duration of response (DoR) form the primary basis of the FDA's regulatory decision, and BICR-assessed ORR was comparable in all three arms at 31%-32% with 95% confidence interval [CI] 18%-47%. The DoR ranged from 17.5 to 22.2 months across the three arms, with overlapping 95% CIs. Adverse events (AEs) were generally consistent with the known AE profiles of nivolumab and ipilimumab, and no new safety events were identified. This article summarizes the FDA review of the data supporting the approval of nivolumab and ipilimumab for the treatment of HCC. IMPLICATIONS FOR PRACTICE: Nivolumab and ipilimumab combination therapy is another option for patients with advanced hepatocellular carcinoma who experience radiographic progression during or after sorafenib or sorafenib intolerance. No new toxicities were identified, but, as expected, increased toxicity was observed with the addition of ipilimumab to nivolumab as compared with nivolumab alone, which is also approved for the same indication. Whether to administer nivolumab as a single agent or in combination with ipilimumab is expected to be a joint decision between the oncologist and patient, taking into consideration the potential for a higher likelihood of response and the potentially higher rate of toxicity with the combination.

Target Adverse Event Profiles for Predictive Safety in the Postmarket Setting.

We improved a previous pharmacological target adverse-event (TAE) profile model to predict adverse events (AEs) on US Food and Drug Administration (FDA) drug labels at the time of approval. The new model uses more drugs and features for learning as well as a new algorithm. Comparator drugs sharing similar target activities to a drug of interest were evaluated by aggregating AEs from the FDA Adverse Event Reporting System (FAERS), FDA drug labels, and medical literature. An ensemble machine learning model was used to evaluate FAERS case count, disproportionality scores, percent of comparator drug labels with a specific AE, and percent of comparator drugs with the reports of the event in the literature. Overall classifier performance was F1 of 0.71, area under the precision-recall curve of 0.78, and area under the receiver operating characteristic curve of 0.87. TAE analysis continues to show promise as a method to predict adverse events at the time of approval.

Predicting potential adverse events using safety data from marketed drugs.

BACKGROUND: While clinical trials are considered the gold standard for detecting adverse events, often these trials are not sufficiently powered to detect difficult to observe adverse events. We developed a preliminary approach to predict 135 adverse events using post-market safety data from marketed drugs. Adverse event information available from FDA product labels and scientific literature for drugs that have the same activity at one or more of the same targets, structural and target similarities, and the duration of post market experience were used as features for a classifier algorithm. The proposed method was studied using 54 drugs and a probabilistic approach of performance evaluation using bootstrapping with 10,000 iterations. RESULTS: Out of 135 adverse events, 53 had high probability of having high positive predictive value. Cross validation showed that 32% of the model-predicted safety label changes occurred within four to nine years of approval (median: six years). CONCLUSIONS: This approach predicts 53 serious adverse events with high positive predictive values where well-characterized target-event relationships exist. Adverse events with well-defined target-event associations were better predicted compared to adverse events that may be idiosyncratic or related to secondary target effects that were poorly captured. Further enhancement of this model with additional features, such as target prediction and drug binding data, may increase accuracy.

Target-Adverse Event Profiles to Augment Pharmacovigilance: A Pilot Study With Six New Molecular Entities.

Clinical trials can fail to detect rare adverse events (AEs). We assessed the ability of pharmacological target adverse-event (TAE) profiles to predict AEs on US Food and Drug Administration (FDA) drug labels at least 4 years after approval. TAE profiles were generated by aggregating AEs from the FDA adverse event reporting system (FAERS) reports and the FDA drug labels for drugs that hit a common target. A genetic algorithm (GA) was used to choose the adverse event (AE) case count (N), disproportionality score in FAERS (proportional reporting ratio (PRR)), and percent of comparator drug labels with an AE to maximize F-measure. With FAERS data alone, precision, recall, and specificity were 0.57, 0.78, and 0.61, respectively. After including FDA drug label data, precision, recall, and specificity improved to 0.67, 0.81, and 0.71, respectively. Eighteen of 23 (78%) postmarket label changes were identified correctly. TAE analysis shows promise as a method to predict AEs at the time of drug approval.

Improving drug safety with a systems pharmacology approach.

Systems pharmacology is used to mechanistically analyze drug-adverse drug reaction (ADRs) pairs and is a promising solution to the complex problem of understanding mechanisms of toxicity. In this research, we have explored the feasibility of retrospectively mapping population-level adverse events from the FDA Adverse Event Reporting System (FAERS) to chemical and biological databases to identify drug safety signals and the underlying molecular mechanisms. We used an analytic platform - Molecular Analysis of Side Effects (MASE™). For this purpose, we selected the adverse event of severe and potentially fatal cutaneous reactions (SCARs) that are associated with acetaminophen (APAP). SCARs encompass the continuum between Stevens-Johnson Syndrome (SJS) and Toxic Epidermal Necrolysis (TEN). We found a statistically significant association between APAP and TEN, the most severe form of SCARs. We also explored the influence of APAP on other classes of drugs commonly associated with SCARs. We found that APAP significantly reduced the risk of SCARs commonly associated with carbamazepine (CBZ). We used molecular docking simulations to propose a mechanism for APAP's reduction in CBZ-induced SCARs which is competitive inhibition of the binding of CBZ to HLA-B*15:02. We conclude that systems pharmacology can complement established surveillance methodologies by providing a means to undertake an independent investigation and review of the mechanisms by which drugs cause adverse events.

Novel insights into the regulation of the timeless protein.

In the Drosophila circadian clock, period (per) and its partner, timeless (tim), play a central role in the negative limb of an autoregulatory feedback loop. Unlike per, the dosage of which affects the frequency (tau) of the circadian cycle, we found that increasing copies of the tim gene has no effect on clock period length. The use of the tim promoter to express per results in a shortening of circadian period, also indicating that the regulation of tim is different from that of per. Drosophila TIM is similar to the mammalian circadian protein mPER2 in that it shuttles independently between the nucleus and cytoplasm both in vivo and in vitro. Contrary to the current model that PER and TIM heterodimerization is a prerequisite for their nuclear entry, PER is not required to transport TIM into nuclei, although it influences TIM localization and vice versa. Blocking nuclear export led to increased nuclear expression of TIM in S2 cells and in wild-type and per01 larvae, suggesting that PER may be required for nuclear retention of TIM. Unlike PER, nuclear TIM alone has no ability to repress transcription. We propose that TIM drives cycles of PER expression by regulating its stability, and in turn, PER retains TIM in the nucleus, either for the regulation of its own stability or for a novel nuclear role of TIM.

Restoration of circadian behavioural rhythms in a period null Drosophila mutant (per01) by mammalian period homologues mPer1 and mPer2.

BACKGROUND: Recent molecular studies suggest that mammals and Drosophila utilize similar components to generate circadian (approximately equal to 24 h) rhythms. The first identified circadian clock gene, the period (per) gene, is indispensable for behavioural rhythms in Drosophila and is represented in mammals by three orthologues, the relative roles of which are not known. In this study, we investigated the functional conservation of per by introducing the mouse mPer1 and mPer2 genes, driven by the Drosophila timeless (tim) promoter, into Drosophila melanogaster. RESULTS: Behavioural assays showed that both mPer constructs restored rhythms in per(01) flies that are otherwise arrhythmic due to a lack of endogenous per protein (PER). However, the rhythms restored by mPer2 were generally stronger and differed in periodicity from those restored by mPer1. In rhythmic transgenic flies, mPER proteins were expressed in lateral neurones and/or many cells in optic lobe. In addition, cell culture experiments indicated that the Drosophila PER partner, TIM, can form a complex with each of these two mammalian proteins. CONCLUSIONS: This study demonstrates that both mPer1 and mPer2 can function as clock components, and has implications for a functional analysis of the different per genes.