Dealing With The Challenges Of Drug Discovery

Is the Traditional Drug Discovery Process Holding Back Your Pipeline?

In the fast-paced world of drug discovery, the traditional process has become a significant bottleneck, hampering innovation and delaying the delivery of life-saving treatments. This article explores two major flaws in the conventional drug discovery approach that are at the root of the challenges faced by pharma and biotech companies today: the over-reliance on in vitro models and the lengthy development cycles associated with mammalian models. We’ll highlight how these issues are driving a shift towards alternative strategies that could reshape early-stage screening in drug discovery.

Key Challenges of the Conventional Drug Discovery Process

1. Long Timelines

The journey from drug discovery to market approval is notoriously long, with preclinical and clinical phases being the major culprits behind these delays. The preclinical phase alone, which heavily relies on traditional animal models, can take between 3 to 6 years to complete. Despite the significant time investment, only about 10% of drug candidates successfully transition from preclinical to clinical trials, according to the Biotechnology Innovation Organization (BIO) [1]. 

This low success rate highlights a critical flaw: conventional animal models are not only slow and costly but also offer limited predictive power for human outcomes. The inefficiency of this approach underscores the pressing need for more reliable, faster, and cost-effective early-stage approaches that can better predict clinical success and streamline the drug development process [1].

2. High Costs

The financial burden of drug development is a major barrier, with the average cost of bringing a new drug to market ranging from $985 million to over $2.8 billion, especially in complex areas like oncology [2]. A significant portion of these costs arises during the preclinical phase, with preclinical costs ranging between $1 - $6 million. This is due to traditional animal models requiring extensive resources, including high-maintenance facilities, specialized care, and lengthy testing protocols [3].

The expense is further amplified by the need for repeated studies to account for variability in results, as traditional models often need more consistency for reliable data. These high costs place immense strain on R&D budgets, limiting the number of compounds that can be explored and slowing down the pace of innovation.

3. High Failure Rates in Clinical Trials

One of the most concerning statistics in drug discovery is that nearly 90% of drugs entering clinical trials fail to reach the market. Most failures are due to a lack of efficacy, which often stems from inadequate insights provided by in vitro models, small sample sizes in mammalian models, and the limited translatability of the data these models generate. These challenges highlight a critical gap in the drug development process, where a more predictive and informative early-stage model could significantly impact.

Critical Issues in the Conventional Approach

1. Over-Reliance on In Vitro Models

In vitro models are a staple in the early stages of drug discovery, providing a controlled environment for initial screenings. However, these models lack the complexity of an entire organism, failing to replicate the multicellular interactions, developmental processes, and complex disease phenotypes found in vivo. 

Therefore, the over-reliance on in vitro data can lead to low-informative readouts that do not translate effectively into clinical success. The limited functional insights offered by these models often cause the high attrition rates seen in drug development.

2. Lengthy Development Cycles with Mammalian Models

Once compounds advance beyond in vitro testing, they are typically evaluated using mammalian models such as rodents. While these models provide more comprehensive data, they are slow, costly, and require extensive use of animals, raising ethical concerns.

The emergence of advanced therapies, such as gene and cell therapies, has further highlighted the limitations of these models, as they struggle to keep pace with the need for high-throughput and personalized screening capabilities. This reliance on traditional mammalian models contributes to prolonged development cycles and increases the financial burden of drug discovery.

Shifting Towards Alternative Models

The challenges associated with conventional drug discovery methods have spurred the development of new approaches that aim to refine early-stage screening. Emerging technologies and alternative models are increasingly being integrated into drug discovery strategies. Innovations such as organ-on-a-chip systems, humanized models, and in vivo models with high-throughput capabilities are reshaping the preclinical landscape, offering the potential to generate actionable data faster and more efficiently.

Among the emerging alternatives, zebrafish stand out for their unique combination of in vivo insights and high-throughput capabilities similar to in vitro models. As a small vertebrate, zebrafish provide a whole-organism context that captures complex biological interactions, offering early functional data that cannot be obtained from cell cultures alone. Integrating zebrafish into preclinical workflows allows researchers to conduct efficient, large-scale screenings while maintaining the depth of in vivo analysis.

This approach not only enhances the predictive power of early-stage testing but also leads to better decision-making in the selection of compounds or therapeutic targets. Thus, fewer compounds progress to costly mammalian studies, streamlining the overall drug discovery process. As a result, zebrafish integration in early-stage screening would reduce dependency on slow, resource-intensive mammalian models.

Regulatory Trends Supporting Alternative Models

Regulatory agencies like the EMA and FDA are increasingly advocating for the use of alternative models to support ethical research practices. The push for the "3Rs"—Replacement, Reduction, and Refinement—urges researchers to minimize animal use wherever possible [4]. 

This shift is not only driven by ethical considerations but also aims to streamline the drug development process, making it more efficient and cost-effective. As the industry moves towards more integrated approaches, alternative models like zebrafish are becoming key components in preclinical screening strategies, offering insights that guide more resource-intensive mammalian studies [5].

Conclusion

The traditional drug discovery process, with its over-reliance on in vitro models and lengthy mammalian testing, presents significant challenges that can impede progress and inflate costs. As the industry evolves, there is a growing recognition of the need for valuable intermediary models that can refine early-stage screening.

By incorporating alternative models such as zebrafish, researchers can gain functional, in vivo insights early in the drug discovery pipeline, ultimately enhancing the predictability of preclinical testing and reducing the overall burden on time and resources. Embracing these innovative approaches could be the key to overcoming the inefficiencies of traditional methods and accelerating the development of new therapies.

REFERENCES

[1] Biotechnology Innovation Organization (BIO). Clinical Development Success Rates and Contributing Factors 2011-2020. Retrieved from: https://www.bio.org

[2] DiMasi, J. A., Grabowski, H. G., & Hansen, R. W. (2016). Innovation in the pharmaceutical industry: New estimates of R&D costs. Journal of Health Economics, 47, 20-33.

[3] Paul, S. M., et al. (2010). How to improve R&D productivity: the pharmaceutical industry's grand challenge. Nature Reviews Drug Discovery, 9(3), 203-214.

[4] European Medicines Agency (EMA). The 3Rs: Replacement, Reduction, and Refinement. Retrieved from: https://www.ema.europa.eu

By Miriam Martínez

Miriam is a Human Biologist expert in neuropharmacology. After a master’s degree in Pharmaceutical and Biotech Industry, she obtained her PhD in Biomedicine from Pompeu Fabra University (Barcelona). During her doctorate, she focused her research on the behavioral analysis of animal models for neurophenotypical characterization. Since then, she has been working in the healthcare marketing and publicity sector, where she has contributed to developing marketing campaigns for several pharmaceutical brands. In 2021, she joined ZeClinics with a branding and marketing strategy focus.