Drug Discovery and Development: A Step-By-Step Process

The Drug Discovery and Development Process: Context and Functions

The drug discovery and development process is critical and complex, involving multiple stages designed to ensure the safety and efficacy of new therapies. From target identification in drug discovery to market approval, a new medicine typically requires 12-15 years. The financial investment needed to develop a New Molecular Entity (NME) exceeds US $1 billion. On average, estimates place the cost around US $2.8 billion.

The drug discovery process begins with an unmet medical need—when no adequate treatment exists for a particular disease or the existing therapies are not powerful enough. The first step is to analyze biological mechanisms and determine how modifying a specific protein or pathway could produce a therapeutic effect. Once a suitable target is identified, further validation may be required before progressing to the next stage.

During the drug discovery process, small-molecule compounds or biological therapies are screened to identify initial candidates acting on the target, known as hits. These hits are refined into leads, which have improved drug-like properties. Once promising leads are identified, lead optimization in drug discovery enhances their potency, selectivity, and pharmacokinetic profile to ensure they meet therapeutic requirements, revealing potential drug candidates. 

If promising, drug development starts with these candidates progressing through pre-clinical research, followed by clinical testing, with the ultimate goal of reaching the market as an approved treatment.

Figure 1. Phases of the drug discovery and development process. ADME: absorption, distribution, metabolism, and excretion; High-Throughput Screening; IND: Investigational New Drug; HTS: ND: New Drug

The Five Steps of the Drug Discovery Process

These are the five steps of new drug discovery: 

1. Early Drug Discovery 

Early drug discovery starts with strategic research to identify proteins, genes, or pathways as therapeutic targets. Further target validation ensures that acting on the selected biomolecule has a therapeutic effect. 

Thousands of compounds are then screened using high-content screening, high-throughput screening, or virtual screening. These popular screening solutions for drug discovery assist in finding hits that interact with the target. These hits undergo the hit-to-lead phase for lead identification, where promising candidates are refined based on potency, selectivity, and biological activity. 

Subsequently, leads are optimized by modifying them to improve pharmacokinetics, efficacy, and safety, with absorption, distribution, metabolism, and excretion (ADME) assessments ensuring drug-like properties. In vitro models, like cell culture, help analyze drug metabolism profiles and interactions. Incorporating alternative models like zebrafish, which provide whole-organism insights and genetic similarities to humans, enhances candidate selection. By narrowing down viable candidates before transitioning to preclinical studies in traditional animal models, researchers can reduce costs and minimize the need for animal testing.

2. Pre-clinical Phase

Preclinical studies bridge the gap between drug discovery and initiating first in human studies. Selected lead compounds are rigorously tested to evaluate their key parameters such as ADME, as well as efficacy and safety using animal models, such as rodents. These studies provide critical data on how the drug behaves in the human body and help detect potential toxicities that could impact clinical trial safety.

3. Clinical Phase 

The clinical phase in the drug development process comprises clinical trials in humans. Before starting a clinical trial, an Investigational New Drug (IND) application is submitted to regulatory agencies, such as the Food and Drug Administration (FDA) in the United States or the European Medicines Agency (EMA) in Europe. This includes: animal efficacy data and toxicity gathered at pre-clinical studies, manufacturing information, and clinical protocols proposed for the clinical trials. 

If it is approved, the clinical trial starts and the candidate drugs advance to the following phases: 

• Phase I: A small group of healthy volunteers (20-100 people) receives the drug to evaluate safety and pharmacokinetics, dosage, absorption, metabolism, and elimination, as well as possible side effects. 
• Phase II: The drug is administered to 100-500 patients with the target disease to analyze the optimal dose and assess efficacy, and potential side effects. Phase IIa involves drug dose refinement to provide the desired therapeutic effect. This dose is then tested in Phase IIb where the overall efficacy of the candidate drugs is examined relative to the current standard of care or the placebo. 
• Phase III: Large-scale clinical trials, involving 300 to 3,000 people, confirm the drug’s effectiveness and monitor long-term and rare adverse effects across diverse patient populations.

Figure 2. Stimate duration, cost percentage, and probability of success of the steps of drug discovery and development process. NME: New Molecular Entity. Adapted from: Sun, D., Gao, W., Hu, H., & Zhou, S. (2022). Why 90% of clinical drug development fails and how to improve it? Acta Pharmaceutica Sinica B, 12(7), 3049–3062

4. Regulatory Approval 

Following successful clinical trial phase III, a New Drug Application (NDA) is submitted to regulatory authorities. This step involves an extensive review of clinical data, manufacturing processes, and labeling to ensure the drug meets safety and efficacy standards. The drug has to have a favorable “risk-benefit ratio”. These reviews, which can usually take 1-2 years, if successful lead to regulatory approval. 

5. Post-market Safety Monitoring 

Approval is not the last step of the drug development process. Regulatory agencies usually require additional follow-up studies, known as phase IV or post-marketing surveillance, with an infinite duration. 

This stage ensures that any rare adverse effects are identified in a much larger population and managed promptly, reinforcing long-term patient safety. It can modify product labeling based on safety observations, contraindications for the use of the new drug in combination with other medications, and in the least favorable outcome, the drug withdrawal from the market. 

Zebrafish as a Key Model in Drug Discovery and Preclinical Testing

Zebrafish (Danio rerio) has become a crucial model in early drug discovery due to their scalability, cost-effectiveness, and ability to provide whole-organism insights. Their transparent embryos and genetic similarity to humans enable real-time observation of biological processes, making them valuable for screening potential drug candidates efficiently.

Zebrafish play a key role in high-content screening (HCS), allowing large-scale, automated testing of compounds for diseases like cancer, cardiovascular conditions, and neurological disorders. Their use in hit-to-lead optimization helps prioritize promising compounds by providing systemic insights that in vitro models lack. During lead optimization, zebrafish aid in refining drug candidates by assessing efficacy and toxicity profiles.

Their ability to absorb compounds directly from water makes them an effective model for toxicity testing, evaluating developmental, cardiovascular, neurological, liver, kidney, and ocular toxicity. This early-stage screening helps eliminate unsafe compounds before they reach costly mammalian testing. By integrating zebrafish into high-throughput screening in drug discovery, toxicity testing, and lead optimization, pharmaceutical research can accelerate the identification of safe and effective drug candidates.

Challenges in Drug Discovery and Development: Strategies for Success

Despite significant advancements, drug discovery challenges remain substantial. High costs, extended timelines, and low-accuracy results can slow progress. Artificial Intelligence (AI) has emerged as a transformative tool, offering faster and more efficient methods to identify promising drug candidates.

AI in drug discovery:

• Accelerates target identification and validation, enabling the analysis of vast genomic and proteomic datasets to uncover disease-related molecules. 
• Helps to predict drug efficacy and toxicity using techniques such as Machine Learning (ML) and Deep Learning (DL) which can analyze large datasets of known drug compounds and identify patterns.
• Predicts the interaction of novel drug pairs by analyzing large datasets of known drug interactions. 
•  Generates novel compounds with optimized properties, enabling rapid and efficient design. 

These advancements reduce costs and increase the success rate of compounds reaching clinical trials.

However, AI faces challenges, such as the need for high-quality, unbiased datasets and the lack of explainability in AI models. While AI cannot replace traditional experimental validation, its integration with laboratory methods is streamlining drug discovery and development, making it a powerful asset in modern pharmaceutical research​. 

Conclusion

The drug discovery and development process requires extensive research, rigorous testing, and significant financial investment. From early drug discovery to post-market surveillance, each phase ensures that new therapies are both effective and safe. Advances in AI-driven drug discovery, high-throughput screening, and alternative models like zebrafish are helping to accelerate and optimize the process, reducing costs and improving success rates. However, challenges such as high failure rates, regulatory barriers, and data limitations remain significant hurdles. By integrating cutting-edge technologies and refining predictive models, the pharmaceutical industry can enhance efficiency and bring innovative treatments to patients faster.

References

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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.

Food and Drug Administration (FDA). Step 3: Clinical Research. Retrieved from: https://www.fda.gov/patients/drug-development-process/step-3-clinical-research#Approval

Hughes, J.P., Rees, S., Kalindjian, S.B., Philpott, K.L. (2011). Principles of early drug discovery. British Journal of Pharmacology, 162(6), 1239-49.

Singh, N., Vayer, P., Tanwar, S., Poyet, J.L., Tsaioun, K., Villoutreix, B.O. (2023). Drug discovery and development: introduction to the general public and patient groups. Frontiers in Drug Discovery, 3,1201419.

Singh, G. (2018). Preclinical drug development. In A. Gad (Ed.), Pharmaceutical medicine and translational clinical research (pp. 47-62). Elsevier. 

Sun, D., Gao, W., Hu, H., & Zhou, S. (2022). Why 90% of clinical drug development fails and how to improve it? Acta Pharmaceutica Sinica B, 12(7), 3049–3062.

By Miriam Martínez

Miriam is a Human Biologist with a strong background in neuropharmacology and a passion for bridging science and innovation. After earning a master’s degree in the Pharmaceutical and Biotech Industry, she completed her PhD in Biomedicine at Pompeu Fabra University (Barcelona), where her research focused on the behavioral analysis of animal models for neurophenotypical characterization. Following her doctoral studies, Miriam transitioned into the healthcare marketing and communication sector, where she played a key role in developing impactful marketing strategies and educational campaigns for leading pharmaceutical brands. She now leverages her scientific expertise, strategic thinking, and creative communication skills in her current role at ZeClinics.