3 ms·

You said in your previous comment that phase II was about finding the "optimal dose" but that testing hospitalization data is not within the scope of phase II.

You said in your previous comment that phase II was about finding the "optimal dose" but that testing hospitalization data is not within the scope of phase II. In a very real-world sense the "optimal dose" is 100% about finding hospitalization/health data. The "optimal dose" in phase II is about the microbiology and isn't very precise in terms of how it translates to real world effects.

mahogany 5y ago
Sure, the phrase "optimal dose" can be dependent on context. Maybe the optimal dose with respect to a decrease in hospitalization turns out to be 79.19 ug, and of course that's not going to be found when you only try 25, 50, 100, and 250. But while a decrease in hospitalization is important, I disagree that it's the only thing that we should be optimizing against. I'm not sure what you mean by health data, but safety and immunogenicity (which might be upstream of hospitalization) are incredibly important to consider in the choice of dosage as well, and that's what optimal dose in the context of trials means. This is the context which I meant it in, and I'm just borrowing this terminology from other places, e.g.: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4944327/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4944327/ https://pubmed.ncbi.nlm.nih.gov/29420118/ https://pubmed.ncbi.nlm.nih.gov/29420118/
- handmodel 5y ago
  After reading your links I think it is more clear that "optimal dose" does not mean optimal dose for the patient or total population. It is optimal dose such that a single phase III trial would detect a measurable effect. Once its approved already at a set dose, the "ideal dose" for future use is probably not the same as the "optimal dose" that maximized probability of approval. "We propose a Bayesian utility approach (BUART) to randomized Phase II clinical trials which uses a first-order bivariate normal dynamic linear model for efficacy and safety in order to determine the optimal dose and study population in a subsequent Phase III clinical trial. "

mahogany 5y ago

Sure, the phrase "optimal dose" can be dependent on context. Maybe the optimal dose with respect to a decrease in hospitalization turns out to be 79.19 ug, and of course that's not going to be found when you only try 25, 50, 100, and 250. But while a decrease in hospitalization is important, I disagree that it's the only thing that we should be optimizing against. I'm not sure what you mean by health data, but safety and immunogenicity (which might be upstream of hospitalization) are incredibly important to consider in the choice of dosage as well, and that's what optimal dose in the context of trials means. This is the context which I meant it in, and I'm just borrowing this terminology from other places, e.g.: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4944327/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4944327/ https://pubmed.ncbi.nlm.nih.gov/29420118/ https://pubmed.ncbi.nlm.nih.gov/29420118/

handmodel 5y ago
After reading your links I think it is more clear that "optimal dose" does not mean optimal dose for the patient or total population. It is optimal dose such that a single phase III trial would detect a measurable effect. Once its approved already at a set dose, the "ideal dose" for future use is probably not the same as the "optimal dose" that maximized probability of approval. "We propose a Bayesian utility approach (BUART) to randomized Phase II clinical trials which uses a first-order bivariate normal dynamic linear model for efficacy and safety in order to determine the optimal dose and study population in a subsequent Phase III clinical trial. "