Impact of biomarker usage on oncology drug development

Background and clinical significance of biomarker-based patient enrichment in non-small-cell lung cancer drug development

Pharmaceutical companies have adopted biomarker-based enrichment (personalized) strategies to improve research and development productivity. We explored the background in which personalized strategies are adopted and examined whether their adoption is linked to improved efficacy of new drugs approved for non-small cell lung cancer (NSCLC) by US Food and Drug Administration (FDA). We extracted data from the first labels of drugs approved for NSCLC between May 2003 and February 2021, and performed a qualitative comparative analysis and meta-analysis. Personalized strategies were adopted in more than half of the trials (16/27) and were often used in trials aimed at obtaining first-line indications and in drugs that were not first-in-class. The meta-analysis showed that personalized trials had significantly improved progression-free survival (PFS) hazard ratio (HR) than trials without personalization but not for relative response rate ratio (RRR) or overall survival (OS) HR. Trials in which PFS HR was the primary endpoint tended to have improved PFS HR, and trials in which OS HR was the primary endpoint had worse PFS HR. The efficacy endpoints that are substantially affected by personalized strategies appear to differ, especially for new drugs with novel mechanism of action (MOA), because trial designs are employed to validate drug-specific advantages.

The Effect of Biomarkers on Clinical Trial Risk in Gastric Cancer

OBJECTIVES

This study examined clinical trial success rates for new drug developments in gastric cancer since 1998. We also examined the clinical trial design features that may mitigate the risk of clinical trial failure.

MATERIALS AND METHODS

Clinical trial data was obtained from clinicaltrials.gov. Drugs were included if they entered testing between January 1, 1998 and January 1, 2022 and were excluded if they did not have a completed phase I trial or treated secondary effects of gastric cancer. Transition probabilities were calculated for each phase and compared with industry averages. Success rates were determined based on biomarker usage, drug target, type of therapy, and drug chemistry.

RESULTS

Upon screening 1990 trials, 219 drugs met our inclusion criteria. The probability of a drug completing all phases of testing and obtaining FDA approval was 7%, which is below the 11% industry average. The use of biomarkers in clinical development resulted in nearly a 2-fold increase in the cumulative success rate. Biologics also exhibited higher success rates (17%) as opposed to small molecules (1%). This was true even when we compared both drug types that shared the same target. When comparing only receptor-targeted therapies, biologics (62%) continued to outperform small molecules (18%). Similarly, when narrowed down to drugs targeting solely HER2 receptors, biologics continued to prevail (64% vs. 24%).

CONCLUSIONS

Implementing biomarkers, receptor-targeted therapies, and biologics in clinical development improves clinical trial success rates in gastric cancer. Thus, physicians should prioritize the enrollment of gastric cancer patients in clinical trials that incorporate the aforementioned features.

The Effect of Biomarker Use on the Speed and Duration of Clinical Trials for Cancer Drugs

Background

The purpose of this study was to explore the effects biomarkers have on the duration and speed of clinical trials in oncology.

Materials and Methods

Clinical trial data was pooled from www.clinicaltrials.gov within the 4 cancer indications of non-small cell lung cancer, breast cancer, melanoma, and colorectal cancer. Heatmaps of clinical timelines were used to display differences in the frequency and timing of clinical trials across trials that used or did not use biomarkers, for all 4 indications.

Results

Screening of 8630 clinical trials across the 4 indications yielded 671 unique drugs corresponding to 1224 eligible trials used in our analysis. The constructed heatmaps visually represented that biomarkers did not have an effect on the time gap between trial phases for non-small cell lung cancer and melanoma but did for colorectal and breast cancer trials, reducing the speed of trial timelines. It was also observed that biomarker trials were more often concurrent over shorter periods of time and began later in the timeline for non-small cell lung and colorectal cancers.

Conclusion

The novel visualization method revealed longer gaps between trial phases, later clinical trial start times, and shorter periods of concurrently run trials for drugs that used biomarkers. The study highlights that biomarker-driven trials might impact drug approval timelines and need to be considered carefully in clinical development plan.

Co-Development of Oncology Drugs and Companion Diagnostics: Analyses of Approval Lags and Drug Development Periods in Recently Approved Cases in Japan

BACKGROUND

The utilization of biomarkers has become increasingly active to enhance efficiency of clinical development. This study evaluated the current situation and quantitative impact of co-development of companion diagnostics (CDx) on the oncology drug development in Japan.

METHODS

Based on publicly available information about the oncology drugs and CDx approved in Japan in 2010-2020, we evaluated the approval lag time between drugs and CDx, and the duration between the pivotal study start date and the new drug application submission date (the time to application). Influences of multiple factors including the use of CDx on the time to application were also analyzed.

RESULTS

A diagnostic test was mostly used from an early development phase such as phase1/2 study, and the median approval lag has tended to decrease when approved CDx were used (- 507 vs. - 25 days for newly developed CDx). The shorter median times to application were observed in Drugs with CDx (1204 days) compared to Targeted therapies without CDx (1423 days) or Other drugs without CDx (1853 days), although both the cancer types and the implementation of multi-regional clinical trials have a larger impact on the time to application compared to the use of CDx.

CONCLUSIONS

The use of CDx from the early development phase and the global development strategy could have a positive contribution on the development period of oncology drugs, which will facilitate patients' earlier access to the optimal treatment.

Does biomarker use in oncology improve clinical trial failure risk? A large-scale analysis

Purpose

To date there has not been an extensive analysis of the outcomes of biomarker use in oncology.

Methods

Data were pooled across four indications in oncology drawing upon trial outcomes from www.clinicaltrials.gov: breast cancer, non‐small cell lung cancer (NSCLC), melanoma and colorectal cancer from 1998 to 2017. We compared the likelihood drugs would progress through the stages of clinical trial testing to approval based on biomarker status. This was done with multi‐state Markov models, tools that describe the stochastic process in which subjects move among a finite number of states.

Results

Over 10000 trials were screened, which yielded 745 drugs. The inclusion of biomarker status as a covariate significantly improved the fit of the Markov model in describing the drug trajectories through clinical trial testing stages. Hazard ratios based on the Markov models revealed the likelihood of drug approval with biomarkers having nearly a fivefold increase for all indications combined. A 12, 8 and 7‐fold hazard ratio was observed for breast cancer, melanoma and NSCLC, respectively. Markov models with exploratory biomarkers outperformed Markov models with no biomarkers.

Conclusion

This is the first systematic statistical evidence that biomarkers clearly increase clinical trial success rates in three different indications in oncology. Also, exploratory biomarkers, long before they are properly validated, appear to improve success rates in oncology. This supports early and aggressive adoption of biomarkers in oncology clinical trials.

Empowering phase II clinical trials to reduce phase III failures

The large number of failures in phase III clinical trials, which occur at a rate of approximately 45%, is studied herein relative to possible countermeasures. First, the phenomenon of failures is numerically described. Second, the main reasons for failures are reported, together with some generic improvements suggested in the related literature. This study shows how statistics explain, but do not justify, the high failure rate observed. The rate of failures due to a lack of efficacy that are not expected, is considered to be at least 10%. Expanding phase II is the simplest and most intuitive way to reduce phase III failures since it can reduce phase III false negative findings and launches of phase III trials when the treatment is positive but suboptimal. Moreover, phase II enlargement is discussed using an economic profile. As resources for research are often limited, enlarging phase II should be evaluated on a case-by-case basis. Alternative strategies, such as biomarker-based enrichments and adaptive designs, may aid in reducing failures. However, these strategies also have very low application rates with little likelihood of rapid growth.

Clinical Equipoise for Trials of Novel Biologic Therapies, Therapeutic Success Rates, and Predictors of Success: A Meta-Analysis

Purpose

The demand for more rapid access to novel biologic therapies than randomized controlled trials can deliver is a topic of ongoing study and debate. We aimed to inform this debate by estimating therapeutic success from phase III trials comparing novel biologic therapies with standard of care and identifying predictors of success.

Methods

This was a meta-analysis of phase III trials evaluating novel biologic therapies in advanced breast, colorectal, lung, and prostate cancers. Therapeutic success was defined as statistically significant results for the primary end point favoring novel biologic therapies.

Results

Of 119 included phase III trials (76,726 patients), therapeutic success was 41%, with a statistically significant relative reduction in disease progression and death for novel biologic therapies over standard of care of 20% and 8%. Therapeutic success did not improve over time (pre-2010, 33%; 2010 to 2014, 44%; P = .2). Predictors of success were a biomarker-selected population (odds ratio, 4.74; 95% CI, 2.05 to 10.95) and progression-free survival end point compared with overall survival (odds ratio, 5.22; 95% CI, 2.41 to 11.39). Phase III trials with a biomarker-selected population showed a larger 28% progression-free survival benefit than phase III trials overall (hazard ratio, 0.72; 95% CI, 0.70 to 0.75) but similar 8% overall survival benefit (hazard ratio, 0.92; 95% CI, 0.90 to 0.94). Therapeutic success of phase III trials with and without a preceding phase II trial were 43% and 30%, respectively

Conclusion

Therapeutic success of novel biologic therapies in phase III trials, including therapies with a matching predictive biomarker, was modest and has not significantly improved over time. Equipoise remains and supports the ongoing ethical and scientific requirement for phase III randomized controlled trials to estimate treatment efficacy and assess the value of potential biomarkers.

Imatinib treatment of poor prognosis mesenchymal-type primary colon cancer: a proof-of-concept study in the preoperative window period (ImPACCT)

Background

The identification of four Consensus Molecular Subtypes (CMS1–4) of colorectal cancer forms a new paradigm for the design and evaluation of subtype-directed therapeutic strategies. The most aggressive subtype - CMS4 - has the highest chance of disease recurrence. Novel adjuvant therapies for patients with CMS4 tumours are therefore urgently needed. CMS4 tumours are characterized by expression of mesenchymal and stem-like genes. Previous pre-clinical work has shown that targeting Platelet-Derived Growth Factor Receptors (PDGFRs) and the related KIT receptor with imatinib is potentially effective against mesenchymal-type colon cancer. In the present study we aim to provide proof for the concept that imatinib can reduce the aggressive phenotype of primary CMS4 colon cancer.

Methods

Tumour biopsies from patients with newly diagnosed stage I-III colon cancer will be analysed with a novel RT-qPCR test to pre-select patients with CMS4 tumours. Selected patients (n = 27) will receive treatment with imatinib (400 mg per day) starting two weeks prior to planned tumour resection. To assess treatment-induced changes in the aggressive CMS4 phenotype, RNA sequencing will be performed on pre- and post-treatment tissue samples.

Discussion

The development of effective adjuvant therapy for primary colon cancer is hindered by multiple factors. First, new drugs that may have value in the prevention of (early) distant recurrence are almost always first tested in patients with heavily pre-treated metastatic disease. Second, measuring on-target drug effects and biological consequences in tumour tissue is not commonly a part of the study design. Third, due to the lack of patient selection tools, clinical trials in the adjuvant setting require large patient populations. Finally, the evaluation of recurrence-prevention requires a long-term follow-up. In the ImPACCT trial these issues are addressed by including newly diagnosed pre-selected patients with CMS4 tumours prior to primary tumour resection, rather than non-selected patients with late-stage disease. By making use of the pre-operative window period, the biological effect of imatinib treatment on CMS4 tumours can be rapidly assessed. Delivering proof-of-concept for drug action in early stage disease should form the basis for the design of future trials with subtype-targeted therapies in colon cancer patients.

Trial registration

ClinicalTrials.gov: NCT02685046. Registration date: February 9, 2016.

Biomarker in Colorectal Cancer

In the last 20 years, improvements in metastatic colorectal cancer treatment lead to a radical raise of outcomes with median survival reaching now more than 30 months. Despite that, the identification of predictive and/or prognostic biomarker still represents a challenging issue, and until today, although clinician and researchers might face with a deeper knowledge of biological mechanisms related to colorectal cancer, many pieces of evidence underline the heterogeneity and the dynamism of such disease. In the present review, we describe the road leading to the discovery of RAS mutations, BRAF V600E mutation, and microsatellite instability role in colorectal cancer; second, we discuss some of the possible major pitfalls of biomarker research, and lastly, we give new suggestions for future research in this field.

Factors associated with failure of oncology drugs in late-stage clinical development: A systematic review

BACKGROUND

We aimed to describe the reasons for failure of experimental anticancer drugs in late-stage clinical development.

MATERIAL AND METHODS

We searched the PharmaProjects database (https://citeline.com/products/pharmaprojects/) for anticancer drugs discontinued between 01/01/2009 and 06/30/2014. Drug programs that reached phase III trials, but never gained Food and Drug Administration (FDA) approval were compared to 37 anti-cancer drugs achieving FDA approval in this time period.

RESULTS

Forty-two drugs fit our criteria for development failures. These failed drugs (49% targeted, 23% cytotoxics, and 28% other) were tested in 43 cancer indications (drug programs). Only 16% (7/43) of failed drug programs adopted a biomarker-driven rationale for patient selection versus 57% (21/37) of successful drug programs (P<0.001). Phase II trial information was available in 32 of 43 failed drug programs and in 32 of 37 successful programs. Nine of the 32 trials (28%) of failed drugs versus 28 of 32 trials (87%) of successful drugs (P<0.001) achieved proof of concept (single agent response rate (RR) ⩾20% or combination therapy showing a ⩾20% RR increase above the median historical RR without the experimental agent (with a minimal absolute increase of 5%) or a randomized phase II trial showing significance (P⩽0.05) for its primary outcome). No pattern of study sites, trial design or funding characteristics emerged from the failed drug analysis.

CONCLUSION

For drugs that reached Phase III, lack of a biomarker-driven strategy and failure to attain proof of concept in phase II are potential risk factors for later discontinuation, especially for targeted agents.

Approaches to modernize the combination drug development paradigm

Recent advances in genomic sequencing and omics-based capabilities are uncovering tremendous therapeutic opportunities and rapidly transforming the field of cancer medicine. Molecularly targeted agents aim to exploit key tumor-specific vulnerabilities such as oncogenic or non-oncogenic addiction and synthetic lethality. Additionally, immunotherapies targeting the host immune system are proving to be another promising and complementary approach. Owing to substantial tumor genomic and immunologic complexities, combination strategies are likely to be required to adequately disrupt intricate molecular interactions and provide meaningful long-term benefit to patients. To optimize the therapeutic success and application of combination therapies, systematic scientific discovery will need to be coupled with novel and efficient clinical trial approaches. Indeed, a paradigm shift is required to drive precision medicine forward, from the traditional "drug-centric" model of clinical development in pursuit of small incremental benefits in large heterogeneous groups of patients, to a "strategy-centric" model to provide customized transformative treatments in molecularly stratified subsets of patients or even in individual patients. Crucially, to combat the numerous challenges facing combination drug development-including our growing but incomplete understanding of tumor biology, technical and informatics limitations, and escalating financial costs-aligned goals and multidisciplinary collaboration are imperative to collectively harness knowledge and fuel continual innovation.

Predictors of chemotherapy efficacy in non-small-cell lung cancer: a challenging landscape

BACKGROUND

Conventional cytotoxic chemotherapy (CCC) is the backbone of non-small-cell lung cancer (NSCLC) treatment since decades and still represents a key element of the therapeutic armamentarium. Contrary to molecularly targeted therapies and immune therapies, for which predictive biomarkers of activity have been actively looked for and developed in parallel to the drug development process ('companion biomarkers'), no patient selection biomarker is currently available for CCC, precluding customizing treatment.

MATERIALS AND METHODS

We reviewed preclinical and clinical studies that assessed potential predictive biomarkers of CCC used in NSCLC (platinum, antimetabolites, topoisomerase inhibitors, and spindle poisons). Biomarker evaluation method, analytical validity, and robustness are described and challenged for each biomarker.

RESULTS

The best-validated predictive biomarkers for efficacy are currently ERCC1, RRM1, and TS for platinum agents, gemcitabine and pemetrexed, respectively. Other potential biomarkers include hENT1 for gemcitabine, class III β-tubulin for spindle poisons, TOP2A expression and CEP17 duplication (mostly studied for predicting anthracyclines efficacy) whose applicability concerning etoposide would deserve further evaluation. However, none of these biomarkers has till now been validated prospectively in an appropriately designed and powered randomised trial, and none of them is currently ready for implementation in routine clinical practice.

CONCLUSION

The search for predictive biomarkers to CCC has been proven challenging. If a plethora of biomarkers have been evaluated either in the preclinical or in the clinical setting, none of them is ready for clinical implementation yet. Considering that most mechanisms of resistance or sensitivity to CCC are multifactorial, a combinatorial approach might be relevant and further efforts are required.

Failures in Phase III: Causes and Consequences

Phase III randomized controlled trials (RCT) in oncology fail to lead to registration of new therapies more often than RCTs in other medical disciplines. Most RCTs are sponsored by the pharmaceutical industry, which reflects industry's increasing responsibility in cancer drug development. Many preclinical models are unreliable for evaluation of new anticancer agents, and stronger evidence of biologic effect should be required before a new agent enters the clinical development pathway. Whenever possible, early-phase clinical trials should include pharmacodynamic studies to demonstrate that new agents inhibit their molecular targets and demonstrate substantial antitumor activity at tolerated doses in an enriched population of patients. Here, we review recent RCTs and found that these conditions were not met for most of the targeted anticancer agents, which failed in recent RCTs. Many recent phase III RCTs were initiated without sufficient evidence of activity from early-phase clinical trials. Because patients treated within such trials can be harmed, they should not be undertaken. The bar should also be raised when making decisions to proceed from phase II to III and from phase III to marketing approval. Many approved agents showed only better progression-free survival than standard treatment in phase III trials and were not shown to improve survival or its quality. Introduction of value-based pricing of new anticancer agents would dissuade the continued development of agents with borderline activity in early-phase clinical trials. When collaborating with industry, oncologists should be more critical and better advocates for cancer patients.

Chronic Activation of Innate Immunity Correlates With Poor Prognosis in Cancer Patients Treated With Oncolytic Adenovirus

Despite many clinical trials conducted with oncolytic viruses, the exact tumor-level mechanisms affecting therapeutic efficacy have not been established. Currently there are no biomarkers available that would predict the clinical outcome to any oncolytic virus. To assess the baseline immunological phenotype and find potential prognostic biomarkers, we monitored mRNA expression levels in 31 tumor biopsy or fluid samples from 27 patients treated with oncolytic adenovirus. Additionally, protein expression was studied from 19 biopsies using immunohistochemical staining. We found highly significant changes in several signaling pathways and genes associated with immune responses, such as B-cell receptor signaling (P < 0.001), granulocyte macrophage colony-stimulating factor (GM-CSF) signaling (P < 0.001), and leukocyte extravasation signaling (P < 0.001), in patients surviving a shorter time than their controls. In immunohistochemical analysis, markers CD4 and CD163 were significantly elevated (P = 0.020 and P = 0.016 respectively), in patients with shorter than expected survival. Interestingly, T-cell exhaustion marker TIM-3 was also found to be significantly upregulated (P = 0.006) in patients with poor prognosis. Collectively, these data suggest that activation of several functions of the innate immunity before treatment is associated with inferior survival in patients treated with oncolytic adenovirus. Conversely, lack of chronic innate inflammation at baseline may predict improved treatment outcome, as suggested by good overall prognosis.

Association between α-synuclein blood transcripts and early, neuroimaging-supported Parkinson's disease

There are no cures for neurodegenerative diseases and this is partially due to the difficulty of monitoring pathogenic molecules in patients during life. The Parkinson's disease gene α-synuclein (SNCA) is selectively expressed in blood cells and neurons. Here we show that SNCA transcripts in circulating blood cells are paradoxically reduced in early stage, untreated and dopamine transporter neuroimaging-supported Parkinson's disease in three independent regional, national, and international populations representing 500 cases and 363 controls and on three analogue and digital platforms with P < 0.0001 in meta-analysis. Individuals with SNCA transcripts in the lowest quartile of counts had an odds ratio for Parkinson's disease of 2.45 compared to individuals in the highest quartile. Disease-relevant transcript isoforms were low even near disease onset. Importantly, low SNCA transcript abundance predicted cognitive decline in patients with Parkinson's disease during up to 5 years of longitudinal follow-up. This study reveals a consistent association of reduced SNCA transcripts in accessible peripheral blood and early-stage Parkinson's disease in 863 participants and suggests a clinical role as potential predictor of cognitive decline. Moreover, the three independent biobank cohorts provide a generally useful platform for rapidly validating any biological marker of this common disease.

Biomarker use is associated with reduced clinical trial failure risk in metastatic melanoma

Given the high morbidity and mortality associated with metastatic melanoma, considerable attention has been paid to identifying potential therapies. Until recently, few therapies have been specifically approved for treating metastatic melanoma. In an attempt to increase clinical trial successes, many therapies are implementing biomarkers for patient stratification. This strategy narrows down the population in an effort to identify appropriate subpopulations that have increased efficacy or fewer safety concerns. However, the addition of a biomarker constitutes an additional risk to clinical development and may therefore increase the overall clinical trial risk. Here, we examine the clinical trial success rate for therapies targeting metastatic melanoma. In addition, we identify the impact that biomarkers have had on the clinical development of this disease.

Molecular biomarkers in clinical development: what could we learn from the clinical trial registry?

Aim: Objective of this research is to assess whether the trend of stratified medicine widely discussed in scientific literature is translated into real clinical trials registered in ClinicalTrials.gov . Methods: By semi-automatic screening of over 150,000 trials, we filtered trials with stratified biomarker to analyze their therapeutic focus, major drivers and elucidated the impact of stratified biomarker programs on trial duration and completion. Results: >5% of trials are using molecular biomarker for stratification; duration of such trials is longer. 21% of them are done in late stages and Oncology is the major focus. Conclusion: Trials with stratified biomarker in drug development has quadrupled in last decade but represents a small part of all interventional trials reflecting multiple co-developmental challenges of therapeutic compounds and companion diagnostics.

Impact of biomarkers on clinical trial risk

The last decade has witnessed the cost of drug development rise dramatically; concurrently, the number of new drug approvals has declined. Clinical trial failure rates have contributed significantly to this 'innovation' crisis and are directly related to clinical trial risk. One strategy that is often touted to resolve this challenge depends on embracing a personalized medicine approach where treatment is tailored to a patient's unique genetic background. We highlight a new risk-based paradigm of clinical trial risk that evaluates the utility of biomarkers in drug development and their risk mitigation benefits. Furthermore, examples elucidating the current state of biomarker integration during clinical trials and the potential risks posed by doing so will be discussed.