Five Ways to Reduce Clinical Trial Costs from Bench to Bedside

Tuesday, November 1, 2022

Drug developers set their clinical trials up for success by increasing efficiency and collecting better data

Jeremiah McDole- Oncology Segment Manager, Bio-Rad Labs

A 2020 study reported the median cost to develop an on-market drug in the US was approximately $1.1 billion, reflecting a range between $314 million and $2.8 billion.1

Only 9.6% of new molecular entities (NME), those that demonstrate a clear clinical benefit and tolerable side-effect profile, eventually make it to market.2 For the relatively few NMEs that have come to market in recent years, most failed in clinical trials at a prodigious expense. The cost of these failures strains drug developers and is passed on, burdening both consumers and healthcare systems. Therefore, it is paramount that companies continue to seek new ways to improve drug development and clinical trial efficacy.

A number of factors drive up drug approval costs, including:3

  • Failing too slowly
  • Poor quality control
  • Large patient cohorts
  • Frequent patient travel
  • Time conducting human trials

This article will explore these pain points as well as ways cutting-edge strategies and technologies can be introduced to reduce the undue burden created by these factors.

Fine-Tuning Preclinical Studies

Traditionally, preclinical research primarily occurs through in vitro experiments, while animal models are used to carry out toxicology experiments. Using these model systems for preclinical research comes with a fundamental flaw: they struggle to replicate human physiology.

Indeed, animal models have been heavily scrutinized in the past decade because they are very expensive and only predict toxicity in humans with 50% accuracy.4 Therefore, even if preclinical experiments generate promising results from experiments performed on cell cultures, rats, pigs, or dogs, it may not be possible to replicate these results in human subjects. As paradoxical as it sounds, drug developers could save time and money by failing faster: by using lab-designed model systems, they can test for fundamental flaws in drug candidates before running experiments on expensive test subjects.

For example, NMEs can be tested against organs-on-a-chip and organoids, which are capable of mimicking specific human physiological systems in a preclinical setting.5 In one study, scientists grew organoids derived from neurons of patients with a rare pain disorder to conduct various measurements of neuronal activity. Results revealed a promising therapeutic candidate with the potential to relieve severe, chronic pain associated with the disorder.6 While these lab-designed model systems cannot replace animal models, they can reduce the need for them during some aspects of early drug development.

Furthermore, other approaches, such as computer-based model systems, are under development to help screen drug candidates more easily. For instance, some scientists are using artificial intelligence (AI) during drug discovery. This accelerates the process of screening high volumes of molecules for specific biochemical properties.7,8 Such analysis reduces the number of costly experiments needed to identify a panel of drug candidates.

Improving Quality Control

Now more than ever, drug developers are utilizing cells, viruses, and antibodies to create complex biologic therapeutics. To match pace, developers need a new class of precise and sensitive quality control techniques capable of detecting contaminants while ensuring potency, purity, and consistency within a drug product.

In oncology, ultrasensitive methods of nucleic acid detection are enabling precise and accurate quality control during the manufacturing process of cell and gene therapies, which can vary widely in safety and potency.9 During CAR T cell manufacturing, a chimeric antigen receptor (CAR) transgene is introduced into T cells. The end product may vary in efficacy depending on where the transgene integrates into the cells’ DNA and if the cells are expressing the transgene at target levels. Genetic analysis can establish if cells carry a safe and adequate number of CAR transgenes (between one and four copies) upon administration to patients.10 Similarly, viral vectors used to deliver gene therapies must be highly pure and concentrated while containing few empty capsids.11,12 Highly precise testing helps ensure efficacy, safety, and batch potency, allowing manufacturers to establish proper biological dosages. Finally, cells in the lab are at risk of pathogenic contamination.13 Therefore, manufacturers must test each batch to determine if bacteria or replication-competent viruses are present, which would make the therapy unsafe.

Quantitative PCR (qPCR) is used extensively to conduct quality control testing during drug manufacturing. However, investigators can only interpret qPCR results using a standard curve, and as such, the assay is not sensitive enough to accurately measure minute nucleic acid signals. A newer, more sensitive technology called Droplet Digital PCR (ddPCR) is required to quantify single copies of DNA or cDNA with ultra-precision, highly relevant when manufacturing CAR T cell and gene therapies.14,15 ddPCR assays provide absolute quantification with unmatched sensitivity due to their unique design. These assays distribute and encapsulate a nucleic acid sample across approximately 20,000 droplets, each capable of a PCR reaction. During amplification, dyes or probes fluoresce in droplets containing nucleic acid targets, allowing direct counting of DNA or cDNA strands.

Scientists require increasingly sensitive techniques such as ddPCR technology to verify that complex biologic drugs are safe, effective, and potent. In turn, these techniques promote reliable drug manufacturing that increases efficiency and reduces the chances of setbacks.

Selecting Patient Populations

Somatic mutations are a primary contributor to cancer. Today, clinical trials are generally most effectively and efficiently executed by placing patients according to their mutation profile compared to the anatomical location of the primary cancer.16 Most large medical centers perform broad mutational screening with next generation sequencing (NGS) for patients seeking diagnosis and treatment. If druggable mutations are found, a treating oncologist may either treat the patient with an on-market therapy or enroll them into a clinical trial depending on cancer type, stage, and availability of approved treatments. While NGS provides excellent screening breadth, capable of analyzing hundreds or thousands of mutations with a single assay, a highly sensitive reflex technology should be employed by labs performing this work. Druggable edge cases, situations in which a mutation may or may not be present but analysis is below the limit of detection for NGS, should be reflexed to a technology like ddPCR for conformation. Further, analysis of NGS data can take several days to complete. If results are needed immediately, ddPCR, while limited to roughly a dozen targets per sample well, can provide analysis in the same day.

While the above screening schema is optimal, most patients are still treated in smaller, community settings. Moving these technology platforms into smaller labs will lead to more extensive screening, provide larger available populations for trials. This potentially reduces “open time” of a trial, compressing timelines leading to therapy approval.

Monitoring Patients Remotely

The COVID-19 pandemic vaulted remote patient monitoring technology in clinical trials into common use by offering patients a safer alternative to traveling to hospitals. Since then, remote patient monitoring technology has grown in popularity because it streamlines clinical trial participation and offers precise high-frequency measurements without requiring manual assessments. While remote monitoring can be used for a completely decentralized trial where patients are monitored at their local healthcare facility, it can also help developers strike a middle ground. Remote patient monitoring devices can enable developers to run a hybrid trial in which participants visit the primary facility hosting the trial at major inflection points but otherwise participate near home.

Developers increase patient recruitment and retention by making participation in clinical trials more accessible to more people. Furthermore, by reducing the number of site visits required per patient, drug developers can further reduce staff size and reduce reimbursements for travel, reducing overall clinical trial costs.17

In addition to lowering costs, remote patient monitoring can increase the quality of data captured during a clinical trial. Wearable devices measure and transmit data about a host of vital signs between e-diaries, hospital monitoring stations, and electronic informed consent forms. These processes replace the practice of manually recording measurements in a patient diary, which is notoriously dependent on whether or not the patient accurately recorded each data point in the record.

Looking Forward: Earlier Endpoints

Oncology trials are notoriously costly due to complex protocols and extended enrollment timelines.18 In the future, clinicians hope to reduce these clinical trial costs by establishing more sensitive clinical endpoints that can be achieved more rapidly, shortening trial lengths.19 Trial length plays heavily into cost, particularly at later stages of development when studies occur on a larger scale, with more patients, a more extensive staff, and greater material and site needs. Every trial has an established endpoint - commonly progression-free survival compared to the standard approved therapies - that enables developers to determine whether the treatment in question has the desired therapeutic benefit. However, as the approved therapies become increasingly effective at prolonging life, clinical trials assessing drugs for more significant benefits will have to run for a prohibitively long time to reach the endpoint.

To address this conundrum, researchers are making the case to utilize highly sensitive ctDNA analysis as a proxy biomarker of clinical efficacy.20 By using ddPCR assays to assess each patient's ctDNA status throughout a trial, clinicians predict they will be able to more quickly and accurately measure tumor response. Moreover, this approach is well-suited for ongoing monitoring: ddPCR tests are cheaper and faster than NGS analysis and pose less risk to patients compared to repeated imaging sessions.

Tailoring Your Approach

As the rate of therapeutic innovation in drug development reaches new heights, it becomes increasingly pressing to curb clinical trial length and costs. At every stage of clinical development, researchers, clinicians, manufacturers, and drug developers have the opportunity to contribute to these goals. While the recommendations above can be broadly applied to most trials, every trial design is unique, and tailored approaches to streamlining the clinical trial process may further reduce required resourcing. By simplifying the elaborate planning and experimentation that goes into every clinical trial, developers may reduce their burden, freeing up resources to assess newer NMEs, each with the potential to improve symptoms and extend live expectancy.

References

  1. Wouters OJ, McKee M, Luyten J. Estimated Research and Development Investment Needed to Bring a New Medicine to Market, 2009-2018 [published correction appears in JAMA. 2022 Sep 20;328(11):1111]. JAMA. 2020;323(9):844-853. doi:10.1001/jama.2020.1166
  2. Mullard A. Parsing clinical success rates. Nat Rev Drug Discov. 2016;15(7):447. doi:10.1038/ nrd.2016.136
  3. Moore TJ, Heyward J, Anderson G, Alexander GC. Variation in the estimated costs of pivotal clinical benefit trials supporting the US approval of new therapeutic agents, 2015-2017: a cross-sectional study. BMJ Open. 2020;10(6):e038863. Published 2020 Jun 11. doi:10.1136/ bmjopen-2020-038863
  4. Van Norman GA. Limitations of Animal Studies for Predicting Toxicity in Clinical Trials: Part 2: Potential Alternatives to the Use of Animals in Preclinical Trials. JACC Basic Transl Sci. 2020 Apr;5(4):387-397. doi: 10.1016/j.jacbts.2020.03.010
  5. Wilson C. What lab-grown 'mini-brains' are revealing about this mysterious organ. New Scientist. 2022 July. https://www.newscientist.com/article/mg25533962-300-what-lab[1]grown-mini-brains-are-revealing-about-this-mysterious-organ/. Accessed Sept 22, 2022.
  6. Geha P, Yang Y, Estacion M, et al. Pharmacotherapy for Pain in a Family With Inherited Erythromelalgia Guided by Genomic Analysis and Functional Profiling. JAMA Neurol. 2016;73(6):659-667. doi:10.1001/jamaneurol.2016.0389
  7. Savage N. Tapping into the drug discovery potential of AI. Nature. 2021 May. https://www. nature.com/articles/d43747-021-00045-7. Accessed Sept 22, 2022.
  8. Ayers M, Jayatunga M, Goldader J, Meier C. Adopting AI in Drug Discovery. BCG Publications. 2022 Mar. https://www.bcg.com/publications/2022/adopting-ai-in pharmaceutical-discovery. Accessed Sept 22, 2022.
  9. Wang W. ddPCR in GMP product testing quantifies without calibration curve & determines absolute DNA concentration. Eurofins Newsletter. https://www.eurofins.com/biopharmaservices/product-testing/news-events/newsletters/spring-2021/ddpcr-in-gmp-product testing/. Accessed Sept 22, 2022.
  10. Zhao Y, et al. Development of the First World Health Organization Lentiviral Vector Standard: Toward the Production Control and Standardization of Lentivirus-Based Gene Therapy Products. Hum. Gene Ther. Meth. 28(4): 205-214,2017
  11. Hebben M. (2018). Downstream bioprocessing of AAV vectors: industrial challenges & regulatory requirements. Cell & Gene Ther Ins.4(2), 131-46.
  12. Grieger JC et al. (2016). Production of Recombinant Adeno-associated Virus Vectors Using Suspension HEK293 Cells and Continuous Harvest of Vector from the Culture Media for GMP FIX and FLT1 Clinical Vector. Mol Ther24, 287–297.
  13. Waites K, et al. Mycoplasma pneumoniae from the Respiratory Tract and Beyond. Clin Microbiol Rev 30(3):747-809, 2017.
  14. DeMaio K. (2020). Droplet Digital PCR for AAV Quantitation. Addgene Blog. https://blog. addgene.org/droplet-digital-pcr-for-aav-quantitation.Accessed Sept 22, 2022.
  15. Lu A, et al. Application of droplet digital PCR for the detection of vector copy number in clinical CAR/TCR T cell products. J Transl Med18: 191. 2020.
  16. Cannarile MA, Gomes B, Canamero M, et al. Biomarker Technologies to Support Early Clinical Immuno-oncology Development: Advances and Interpretation. Clin Cancer Res. 2021;27(15):4147-4159. doi:10.1158/1078-0432.CCR-20-2345
  17. Brown C, More than Reduced Costs: The Benefits of Remote Monitoring in Clinical Trials. ANJU Life Sciences Software. 2019 July. https://www.anjusoftware.com/about/all-news/ insights/remote-monitoring#:~:text=Remote%20Trials%20Reduce%20Costs%2C%20 Boosts,Araujo%2C%20founder%20of%20Clinbiz. . Accessed Sept 22, 2022.
  18. Passut C. CenterWatch. 2021 May. https://www.centerwatch.com/articles/25599- oncology-trials-outpacing-rest-of-the-field-in-complexity-and-duration-study[1]shows#:~:text=Consequently%2C%20oncology%20drugs%20accounted%20for,from%20 14.8%20percent%20in%202000. Accessed Sept 22, 2022.
  19. Friends of Cancer Research. Circulating Tumor DNA in Development of Therapies for Cancer: An Evidentiary Roadmap to an Early Endpoint for Regulatory Decision-Making. Discussion Document. https://friendsofcancerresearch.org/wp-content/uploads/ Circulating_Tumor_DNA_in_Development_of_Therapies_for_Cancer-Evidentiary_ Roadmap.pdf. Accessed Sept 22, 2022.
  20. van der Leest P, Hiddinga B, Miedema A, et al. Circulating tumor DNA as a biomarker for monitoring early treatment responses of patients with advanced lung adenocarcinoma receiving immune checkpoint inhibitors [published correction appears in Mol Oncol. 2022 Jan;16(1):310]. Mol Oncol. 2021;15(11):2910-2922. doi:10.1002/1878-0261.13090.

Jeremiah McDole received his Ph.D. in neuroimmunology from the University of Cincinnati and spent his post-doctoral years on a number of successful research projects in the immunology depart at Washington University School of Medicine in St. Louis.

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