How Drug–Diagnostic Co-development is Shaping Discovery Research and Pharmacotherapy

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Published: March 25, 2019

| Faezeh Koohestani & Sasidhar Murikinati, GenScript USA Inc.

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Pairing diagnostic tests that are capable of determining individual patient’s responsiveness to therapeutic options improves the drug development process and drug efficacy. With the rapid growth of technologies focused on identifying disease biomarkers and increasing interest in personalized medicine, the need for designing effective models for parallel development of therapeutics and diagnostics has soared. Consequently, co-development is at the forefront of discovery research laboratories’, pharmaceutical companies’ and regulatory bodies’ efforts. Here, we review the importance and requirements for developing successful drug–diagnostic co-development models. We also highlight current challenges and ongoing efforts to address these issues, bringing us closer towards a more promising future for pharmacotherapy and patient care.

Definition and history of drug–diagnostic co-development

The drug and diagnostic co-development model involves parallel identification, development and testing of a therapeutic and its corresponding diagnostic tool or assay based on the biomarkers (inherited or somatic) of the disease.¹ Co-developed or companion diagnostics (CDx) can predict which patient best responds to the drug, or if they will develop a toxic/adverse reaction against the drug. CDx can also be used to monitor drug response throughout the course of treatment. This enables timely change in dosage and the ability to assess the effectiveness of the drug.² This model is ideal for modern forms of therapy, such as personalized medicine or immunotherapy, where access to an individual’s genetic, proteomic or metabolomics data both enables and necessitates co-development of drugs and corresponding diagnostics.

The idea of combining drugs and diagnostics is not new. When the selective estrogen-receptor modulator tamoxifen was developed in the 1970s for the treatment of breast cancer, data on estrogen-receptor status were correlated with the treatment outcome. Based on a Phase II study performed in patients with advanced breast cancer, published in 1976, the investigators concluded that “a high degree of correlation between response and positive estrogen-receptor assay suggests the value of the diagnostic test as a means to select patients for tamoxifen treatment”.³ Despite the fact that this conclusion was drawn nearly 40 years ago, adaptation of the drug–diagnostic co-development model has been relatively slow; it is only within the last decade that it has gained widespread acceptance. The parallel development of the monoclonal antibody Trastuzumab (Herceptin® , Roche/Genentech) and the CDx assay for HER2 protein overexpression (HercepTest™, Dako) in the 1990s and its successful adoption in clinic seem to have served as inspiration to pharma and biotech companies; the number of drug–diagnostic co-development projects within oncology alone has increased rapidly within the last decade.

Significance and requirements of a drug–diagnostic collaboration

Developing a new drug and bringing it to market is a complex process that takes 12 to 15 years and costs approximately one billion dollars. Co-developing drugs and diagnostics can accelerate regulatory approvals of both while reducing costs. The NSCLC clinical Phase III study is one example where using biomarker-guided drug development increased the success rate from 28% to 62%.⁴

The design and implementation of a successful co-development plan depends on streamlined and interconnected development processes for both the drug and its corresponding mode of diagnostics. While criteria for the development process of an individual drug or diagnostic has long been established in academia and industry, an effective model combining their parallel development has proven to take more than just the merging of steps from the two processes.
In reality, there needs to be a close cross talk between all steps including:⁵

identifying the target and biomarker through R&D,
testing the drug and diagnostic assay or device in preclinical and clinical trials,
obtaining regulatory approval,
manufacturing, and
marketing.

Describing the R&D step of a co-development process can better demonstrate the interconnected relationship in a co-development model. The first step, which involves the development of a biomarker hypothesis, requires a thorough molecular understanding of both the disease pathology and drug mechanism(s) of action. A variety of methodologies such as quantitative PCR (qPCR), DNA sequencing, immunohistochemistry (IHC), in situ hybridization (ISH), proteomics, enumerating circulating tumor cells (CTCs), flow cytometry and arrays are employed in both the development and testing of the hypothesis. However, in order to subject the hypothesis to analytical validation where the accuracy and reliability of the biomarker are measured, data from Phase I/II clinical trials of the drug are required to establish the cut-off value. Therefore, CDx development may not always be useful until sometime has gone by in the drug discovery period. Of course, this scenario is not always possible when the safety of a drug must be tested prior to its efficacy.

On the other hand, while many of the currently-employed methodologies have successfully been used for identifying a druggable target or a biomarker individually, unforeseen shortcomings are observed once they are used in a co-development plan.²

Application of IHC in CDx models is a great example of both the significance and unforeseen challenges in adopting established diagnostic methodologies as companion diagnostics. Widely acknowledged as the superior methodology for analyzing protein expression in all tissue types, IHC has been the tool of choice for companion diagnostic development for a variety of tumors. From breast and pancreatic to gastrointestinal and lung cancers, IHC has been employed to diagnose and monitor response to treatment in estrogen receptor (ER), epidermal growth factor receptor (EGFR) as well as human epidermal growth factor receptor 2 (HER2), to name a few.6 However, results from clinical studies proved that IHC can be a reliable companion diagnostic for trastuzumab (Herceptin) in treating HER2-positive breast cancer patients and also matinib mesylate for gastrointestinal stromal cancer treatment. In other cases, IHC was found to be either not ideal as a predictive biomarker assay or not decisive in determining the clinical response. In spite of such findings and the growing attention to gene-based assays such as next-generation sequencing, IHC is still considered a reliable option for developing CDx. In addition to being time- and cost-effective, IHC can identify disease-specific changes that DNA or RNA-based assays may not detect. Future results will demonstrate how improvements in the co-development process can best utilize the strengths of this assay in combination with other diagnostic tools.

Current status and challenges

Based on the existing and under-modification models, a number of drug–diagnostic co-development projects have already been completed and successfully used in clinics. The following list highlights just four of the approved CDxs:

PD-L1 IHC 22C3 pharmDx for Keytruda (pembrolizimab), developed by DAKO North America Inc. for non-small cell lung cancer, gastric or gastroesophageal junction adenocarcinoma, cervical cancer, and urothelial carcinoma
Bond Oracle HER2 IHC System for Herceptin (trastuzumab), developed by Leica Biosystems for breast cancer
Abbott RealTime IDH1 for Tibsovo (ivosidenib), developed by Abbott Molecular, Inc. for acute myeloid leukemia
FoundationFocus CDxBRCA Assay for Rubraca (rucaparib), developed by Foundation Focus for ovarian cancer

In spite of these successful cases, there are still challenges towards defining a streamlined process with greater rate of success for a variety of diseases beyond cancer.^2,7 One of the biggest challenges is finding the right diagnostics at the right time for clinical trials without imposing additional costs. Another challenge is funding CDx projects, which poses further impediments in recruiting patients for clinical trials. Lack of early engagement in drug–diagnostic co-development models is another major challenge. Logistical issues ranging from pharmaceutical companies not having enough experts in biomarker discovery, optimization and validation to incongruous coordination between pharma and vendors offering diagnostic expertise, can further slow the process. Finally, delayed reimbursement for approved drug–diagnostics in many countries across the globe discourages patients seeking advanced co-development treatments. It is, however, expected that the ongoing efforts of patient advocacy groups, the pharmaceutical industry and regulatory bodies would address these issues.

Choose carefully to facilitate big rewards

With a rising awareness of personalized medicine, growing immunotherapies, and the incidence of cancer and other diseases in the population, there is a need for earlier diagnosis and more personalized treatment options. Companion diagnostics are critical to address this need and drug–diagnostics co-development models offer the best solution to obtain such diagnostics. Greater collaborations among all stake holders in defining and establishing CDx models for a variety of diseases could facilitate the regulatory approval of drug–diagnostics towards faster access to more efficient therapies for patients.

Drug–diagnostics co-development brings together bio-pharmaceutical and diagnostics companies. Based on recent co-development cases, early planning and real-time execution of the co-development process seem to be the key to success. However, selecting the right diagnostics partner for the co-development process is the most critical. Various factors influence the choice of correct partner -- technology heritage, experience with regulatory submissions, global distribution channels, GMP capabilities, supply chain, prioritization in the pipeline, post-launch support and interest for co-development and its timelines. By identifying the right partners and mutual agreement on a co-development model, an effective drug and its companion diagnostic can be offered to patients in less time than the conventional routes at more affordable prices.

References

1. US Food and Drug Administration. Drug–diagnostic Co-Development Concept Paper. Food and Drug Administration website. (2005).

2. Moore, MW. et al. Challenges in the codevelopment of companion diagnostics. Personalized Medicine. 2012; 9(5):485-496.

3. Lerner, HJ. et al. Phase II study of tamoxifen: report of 74 patients with stage IV breast cancer. Cancer Treatment Reports. 1976; 60:1431-5.

4. Falconi, A., et al. Clinical trial risk reduction in non-small cell lung cancer though the use of biomarkers and receptor-targeted therapies. Journal of Clinical Oncology. 2013; 31:8040

5. Olsen, D., & Jørgensen, JT. Companion diagnostics for targeted cancer drugs - clinical and regulatory aspects. Frontiers in Oncology. 2014; 4,105.

6. Gremel, G., et al. In situ Protein Detection for Companion Diagnostics. Frontiers in Oncology. 2013; 31,3:271.

7. Jørgensen, J.T. & Hersom, M. Companion diagnostics—a tool to improve pharmacotherapy. Annals of Translational Medicine, 2016; 4(24): 482.