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Advancing animal testing alternatives
The emerging paradigm: AI prediction → cell models → organoids/chips → minimal animal → human
Several approaches have emerged to reduce the demand on animal models for drug testing. Researchers are rapidly moving beyond traditional animal models by building human-relevant testing systems that better reflect real biology. These include human cell–based models such as primary cells and stem cell–derived tissues, as well as more advanced 3D systems like organoids and spheroids that recreate aspects of organ structure and function. Technologies such as organ-on-a-chip add another layer of realism by simulating dynamic physiological processes—like blood flow or breathing—within microfluidic devices. Alongside these lab-based methods, scientists are increasingly using computational models and AI to predict drug behavior, supported by high-throughput screening and “omics” approaches that provide deep molecular insight. Rather than fully replacing animal studies, these alternatives are converging into a hybrid, human-first testing paradigm. Early-stage discovery often begins with in silico modeling and human cell systems, followed by validation in organoids or chip-based platforms, and in some cases limited animal testing before moving into human trials. This integrated approach improves predictive accuracy, reduces cost and time, and addresses ethical concerns, while also aligning more closely with human physiology. As regulatory agencies begin to recognize these methods, they are poised to become a core foundation of next-generation drug development and biotech innovation.
Newer genetic technology shows promise for less off-target effects on cells
Emerging technology that may replace CRISPR/CAS9 in some instances: A programmable seekRNA guides target selection by IS1111 and IS110 type insertion sequences
https://www.nature.com/articles/s41467-024-49474-9
Biology > Modality (but modality is a proxy) for oncology drug success
Modalities with built-in targeting precision (mAbs, radiopharma, CAR-T) outperform. Modalities relying on systemic biology or immune priming (vaccines, viruses) underperform.
~5%–10% of oncology (cancer) drug candidates that enter Phase I ultimately receive U.S. Food and Drug Administration approval. A commonly referenced large-scale analysis (e.g., BIO/industry reports): ~5.1% overall success rate from Phase I → approval for oncology drugs. This is significantly lower than the industry average across all therapeutic areas (~10–15%). Why is oncology lower? Tumor biology is highly complex and heterogeneous. Endpoints (e.g., survival benefit) are harder to demonstrate. Higher toxicity risk tolerance leads to more early-stage entrants but higher attrition. Many programs fail in Phase II due to lack of efficacy. Stage-by-stage (rough ballpark for oncology): Phase I → Phase II: ~60–70%, Phase II → Phase III: ~25–35%, Phase III → Approval: ~50–70%. So, if you’re modeling biotech value or portfolio risk, only ~1 in 10 (and often closer to 1 in 20) oncology drugs entering Phase I will make it to market. But, this number depends a lot on modality. These differences are a byproduct of biology; the modalities operating on complex or interconnected mechanisms are more likely to fail, whereas targeted approaches are more likely to succeed.
Biotech Venture Capital is Actually Recovering
Post-COVID, biotech funding dipped in 2023 and has seen a modest rebound in recent years relative to other industries.
So, what happened? 2021 peak: Zero rates + COVID biotech tailwinds. Biotech share peaked across all stages. 2022–2023 compression: Rate hikes → late-stage hit hardest. Series C drops most (17% → 13%). 2024–2025 recovery: Reopening IPO window. Capital returns to later-stage biotech. What did we measure? We compute: Biotech % of VC (by stage) = Biotech deal value at stage ⁄ Total VC deal value at stage. Because: Raw SVB reports give biotech totals + stage mix. PitchBook/NVCA give total VC by stage. We normalize across both.
Launch
Altitide's business is in order.
Website is launched after setting up the business essentials. First blog post coming soon.