Eniola's strongest EWOR angle is the founder anomaly, not the technology. The application should open with the audacious data point — a Lagos-based pharmacist who taught herself ML in isolation, derived a drug-resistance predictor from first principles, and achieved 100% mutation coverage where every structure-limited competitor covers only 17.6% — without a lab, without institutional affiliation, without a co-founder. This maps directly onto EWOR's stated archetype: 'outliers who never followed a blueprint.' The €1B+ thesis is then presented as a natural consequence: a single protein-language-model primitive that attacks AMR, oncology, and antivirals simultaneously (EWOR's FAQ explicitly names 'AI for drug discovery' as a flagship fellow use case). The personal statement should resist the temptation to lead with the model — lead instead with the journey of a pharmacist who saw a structural failure in drug discovery (structure-dependency bottleneck) and resolved to fix it unilaterally, because that is the founder story EWOR funds.