Interactive Infographic

The Drug Development Journey

From molecule to medicine: follow a drug through 10-15 years of discovery, testing, and approval - and see how NAMs are transforming every stage

10-15
Years traditional timeline
$2.6B
Average development cost1
90%
Failure rate in trials2
50%
NAMs can reduce time3

Discovery & Target ID

Years 1-4 | Traditional: $500M+

Scientists identify disease targets and screen thousands of compounds to find molecules that might work as drugs. This involves understanding disease biology, identifying druggable targets, and hit-to-lead optimization.

NAMs Impact

  • AI screens millions of compounds in days vs. years
  • In silico models predict binding affinity instantly
  • AlphaFold reveals protein structures for targeting
  • Generative AI designs novel drug candidates
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Preclinical Testing

Years 4-6 | Traditional: $300M+

Drug candidates undergo safety and efficacy testing. Traditionally required extensive animal testing. This stage evaluates toxicity, pharmacokinetics (how the drug moves through the body), and preliminary efficacy.

NAMs Impact

  • Organoids test drug effects on human tissue
  • Organ-on-chip detects liver/cardiac toxicity
  • Multi-organ chips model systemic effects
  • No animals required under FDA Modernization Act 2.0

Clinical Trials

Years 6-12 | Traditional: $1.5B+

Testing in humans proceeds through Phase 1 (safety in healthy volunteers), Phase 2 (efficacy in patients), and Phase 3 (large-scale confirmation). Each phase has strict endpoints and 30-70% failure rates.

NAMs Impact

  • Digital twins optimize patient selection
  • Virtual clinical trials reduce participants needed
  • Patient-derived organoids predict individual responses
  • AI identifies optimal dosing regimens
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FDA Approval & Launch

Years 12-15 | Traditional: $300M+

Regulatory submission, FDA review, and market launch. Companies submit New Drug Applications (NDAs) with all trial data. FDA reviews safety and efficacy before granting approval.

NAMs Impact

  • FDA now accepts NAMs data in regulatory submissions
  • ISTAND program provides guidance on NAMs validation
  • Faster reviews with comprehensive human-relevant data
  • Post-market surveillance via digital twins

Traditional vs. NAMs-Enhanced Development

Metric
Traditional
With NAMs
Timeline
10-15 years
5-8 years
Total Cost
$2.6B1
$800M-1.2B4
Preclinical Accuracy
~50%5
80-90%6
Animals Used
100,000+
Near Zero
Phase 2 Success Rate
29%
45-55%

Clinical Trial Success Rates (Historical)

Discovery → Lead
90%
Phase 1
70%
Phase 2
29%
Phase 3
58%
NDA → Approval
85%

Overall probability: ~10% of drugs entering Phase 1 reach market approval

Simulate the Journey

Experience drug development in our interactive simulations

Drug Predictor Digital Twin Simulator

References

1. Drug Development Cost

DiMasi JA, Grabowski HG, Hansen RW. Innovation in the pharmaceutical industry: New estimates of R&D costs. J Health Econ. 2016;47:20-33. DOI: 10.1016/j.jhealeco.2016.01.012 PMID: 26928437

2. Clinical Trial Failure Rates

Hay M, Thomas DW, Craighead JL, Economides C, Rosenthal J. Clinical development success rates for investigational drugs. Nat Biotechnol. 2014;32(1):40-51. DOI: 10.1038/nbt.2786 PMID: 24406927

3. NAMs Acceleration of Drug Development

Marshall LJ, Troutman J, Walker E, et al. The future of animal-free methods in toxicity testing. ALTEX. 2021;38(4):597-613. DOI: 10.14573/altex.2104051 PMID: 34115141

4. Cost Reduction with NAMs

Low LA, Tagle DA. Organs-on-chips: Progress, challenges, and future directions. Exp Biol Med. 2017;242(16):1573-1578. DOI: 10.1177/1535370217700523 PMID: 28299952

5. Animal Model Predictivity Limitations

Pound P, Ritskes-Hoitinga M. Is it possible to overcome issues of external validity in preclinical animal research? Why most animal models are bound to fail. J Transl Med. 2018;16(1):304. DOI: 10.1186/s12967-018-1678-1 PMID: 30396346

6. Organ-on-Chip Predictive Accuracy

Ingber DE. Human organs-on-chips for disease modelling, drug development and personalized medicine. Nat Rev Genet. 2022;23(8):467-491. DOI: 10.1038/s41576-022-00466-9 PMID: 35286359