Una tradu El Marco de Accesibilidad y Equidad Genómica (GEAF): un marco dimensionalmente coherente para modelar la asequibilidad y la equidad en las terapias genómicas y regenerativas

Resumen

Background

Advances in CRISPR-based gene editing and embryo models derived from mother cells have created important biomedical opportunities, along with considerable ethical and distributive concerns. Personalized genomic and regenerative therapies approved in the United States at the time of writing this work have list prices ranging from approximately $2.2 million (Casgevy) to $4.25 million (Lenmeldy), with several other approved products whose price falls between these figures (e.g., Lyfgenia, $3.1 million; Hemgenix, $3.5 million). It poses the question of how to jointly represent inequality, accessibility, ethical compliance and distributive inequality in a single mathematically coherent index that serves as support for policy analysis.

Methods

We audited a previously proposed composite index, the Genomic Equity Accessibility Framework (GEAF = ((A × E) − (C × I)) / (P + R) × 100), and we identified a dimensional incompatibility between its terms, an output range not allocated and not independently interpretable, and input data from scenarios incoherent with cost estimates cited elsewhere in the same manuscript. We reconstructed the GEAF as a weighted, normalized and scored (0–100) composite of six dimensionless components – accessibility, ethical compliance, equality, equity (inverse inequality), policy solidity and research efficiency –, derived through multi-attribute utility theory. We add the reconstructed formula to tests with extreme algebraic cases, we apply it to a series of re-specified illustrative scenarios whose cost data is anclan in the literature cited on list prices, and we perform univariant, bivariant and probabilistic Monte Carlo sensitivity analyzes (10,000 iterations).

Results

The reconstructed index (GEAF′) is based on [0,100], is monotonous in each component and behaves coherently at algebraic extremes. In several illustrative scenarios, the GEAF′ oscillated between 27.9 (without equity intervention, cost at list price) and 86.5 (fully optimized scaled price and policy scenario). The univariate sensitivity analysis identified the cost (C) and the inequality factor (I) as the biggest determinants of a single index parameter in reference conditions, followed by ethical compliance (E). The Monte Carlo simulation (10,000 iterations per regime), which propagates stated and empirical assumptions of parameter uncertainty, produces an average of 32.6 in the reference scenario (90% range, 5th to 95th percentiles, approximately 22.9–42.9) and an average of 72.4 in the equity intervention scenario (90% range of approximately 62.9–81.1), without undermining between the simulated distributions.

Conclusions

GEAF′ provides a transparent, reproducible and dimensionally coherent way to combine equity, accessibility, ethical compliance and distributive equity in a single comparative index for policy scenarios on genomic and regenerative therapies. It is presented as a candidate conceptual and methodological framework, not as an empirically validated predictive or clinical tool; Quantitative statements about cost reductions in the real world have been eliminated, unless they are supported directly by cited evidence. The prospective empirical calibration with real data on accessibility, prices and policy results is identified as a necessary next step before the GEAF′ is used in the evaluation of health technologies or in resource allocation decisions.

Versão em inglês: https://doi.org/10.1371/journal.pone.0359782