Accelerating model-informed decisions for COVID-19 vaccine candidates using a model-based meta-analysis approach

Kandala, Bhargava; Plock, Nele; Chawla, Akshita; Largajolli, Anna; Robey, Seth; Watson, Kenny; Thatavarti, Raj; Dubey, Sheri; Cheung, S.Y. Amy; Greef, Rik de; Stone, Julie A.; Sachs, Jeffrey R.

doi:10.1016/j.ebiom.2022.104264

Cited by 5 publications

(5 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally, this work relies on predicting vaccine efficacy from neutralization titers. Although this approach has been validated in a number of contexts [15][16][17][21][22][23][24] , it cannot replace clinical studies of vaccine effectiveness. This is especially true given that previous validation of this modelʼs predictions has been for vaccines targeting the ancestral virus.…”

mentioning

confidence: 99%

Predicting the efficacy of variant-modified COVID-19 vaccine boosters

Khoury

Docken

Subbarao

et al. 2023

Nat Med

View full text Add to dashboard Cite

mentioning

confidence: 99%

Predicting the efficacy of variant-modified COVID-19 vaccine boosters

Khoury

Docken

Subbarao

et al. 2023

Nat Med

View full text Add to dashboard Cite

“…Our threshold of 10 3 ED 50 to prevent infection and transmission corresponds to about twofold the peak neutralization value achieved after infection ( Figure ). Other studies 3,24 have shown that a 50% protection against symptomatic disease was achieved with a level of neutralization equivalent to 20% of the mean human convalescent titers. This, therefore, confirms that the level of protection required to prevent infection and transmission is much larger than what is required to prevent symptomatic infection.…”

Section: Discussionmentioning

confidence: 96%

Neutralizing Antibody Levels as a Correlate of Protection Against SARS‐CoV‐2 Infection: A Modeling Analysis

Lingas,

Planas,

Péré

et al. 2023

Clin Pharma and Therapeutics

View full text Add to dashboard Cite

While anti‐SARS‐CoV‐2 antibody kinetics have been described in large populations of vaccinated individuals, we still poorly understand how they evolve during a natural infection and how this impacts viral clearance. For that purpose, we analyzed the kinetics of both viral load and neutralizing antibody levels in a prospective cohort of individuals during acute infection with alpha variant. Using a mathematical model, we show that the progressive increase in neutralizing antibodies leads to a shortening of the half‐life of both infected cells and infectious viral particles. We estimated that the neutralizing activity reached 90% of its maximal level within 11 days after symptom onset and could reduce the half‐life of both infected cells and circulating virus by a 6‐fold factor, thus playing a key role to achieve rapid viral clearance. Using this model, we conducted a simulation study to predict in a more general context the protection conferred by pre‐existing neutralization titers, due to either vaccination or prior infection. We predicted that a neutralizing activity, as measured by ED50 >103, could reduce by 46% the risk of having viral load detectable by standard PCR assays and by 98% the risk of having viral load above the threshold of infectiousness. Our model shows that neutralizing activity could be used to define correlates of protection against infection and transmission.

show abstract

“…MBMA has shown to be useful in both the translation from nonclinical species and predicting human efficacy for vaccines, and this can also extend to include subpopulations such as pregnancy with the right data. 19,43 Discussion and Future There are many opportunities to facilitate more informative planning of translational studies in pregnant women. 44 Both funding opportunities and ongoing clinical trials should provide the source data for this to occur.…”

Section: S58mentioning

confidence: 99%

“…The example of COVID‐19 raises awareness of the need to accelerate vaccine availability globally and deliver it to all populations. MBMA has shown to be useful in both the translation from nonclinical species and predicting human efficacy for vaccines, and this can also extend to include subpopulations such as pregnancy with the right data 19,43 …”

Section: Practice Outcome Impactmentioning

confidence: 99%

Supporting Prospective Pregnancy Trials via Modeling and Simulation: Lessons From the Past and Recommendations for the Future

Cheung

Barrett

2023

The Journal of Clinical Pharma

View full text Add to dashboard Cite

Despite the increasing awareness and guidance to support drug research and development in the pregnant population, there is still a high unmet medical need and off‐label use in the pregnant population for mainstream, acute, chronic, rare disease, and vaccination/prophylactic use. There are many obstacles to enrolling the pregnant population in a study, ranging from ethical considerations, the complexity of the pregnancy stages, postpartum, fetus–mother interaction, and drug transfer to breast milk during lactation and impacts on neonates. This review will outline the common challenges of incorporating physiological differences in the pregnant population and historical but noninformative practice in a past clinical trial in pregnant women that led to labeling difficulties. The recommendations of different modeling approaches, such as a population pharmacokinetic model, physiologically based pharmacokinetic modeling, model‐based meta‐analysis, and quantitative system pharmacology modeling, are presented with some examples. Finally, we outline the gaps in the medical need for the pregnant population by classifying various types of diseases and some considerations that exist to support the use of medicines in this area. Ideas on the potential framework to support clinical trials and collaboration examples are also presented that could also accelerate understanding of drug research and medicine/prophylactics/vaccines in the pregnant population.

show abstract

Accelerating model-informed decisions for COVID-19 vaccine candidates using a model-based meta-analysis approach

Cited by 5 publications

References 49 publications

Predicting the efficacy of variant-modified COVID-19 vaccine boosters

Predicting the efficacy of variant-modified COVID-19 vaccine boosters

Neutralizing Antibody Levels as a Correlate of Protection Against SARS‐CoV‐2 Infection: A Modeling Analysis

Supporting Prospective Pregnancy Trials via Modeling and Simulation: Lessons From the Past and Recommendations for the Future

Contact Info

Product

Resources

About