Could computer models be the key to better COVID vaccines?

Dolgin, Elie

doi:10.1038/d41586-022-00924-8

Cited by 4 publications

(5 citation statements)

References 10 publications

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“…In general, IS/ID modelling offers a promising solution to accelerate how we develop all vaccines [23] . This is especially true of vaccines developed under urgent circumstances, like in the case of COVID-19 where the timely application of IS/ID modelling can vastly improve our ability to protect the global population, saving lives.…”

Section: Discussionmentioning

confidence: 99%

“…To address this, we have launched the novel field of vaccine ‘Immunostimulation/Immunodynamic’ (IS/ID) modelling, an adaptation of methods used in drug development to systematically and quantitatively identify ‘best’ dose. We have shown its potential in a novel TB vaccine [14] , [15] and Adenoviral-based vaccines [16] , [17] , [18] and IS/ID modelling has been recognised by vaccine developers and modellers as the future methodology to optimise vaccine development [19] , [20] , [21] , [22] , [23] .…”

Section: Introductionmentioning

confidence: 99%

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Identifying COVID-19 optimal vaccine dose using mathematical immunostimulation/immunodynamic modelling

Rhodes

Smith²,

Evans³

et al. 2022

Vaccine

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identifying COVID-19 optimal vaccine dose using mathematical immunostimulation/immunodynamic modelling

Rhodes

Smith²,

Evans³

et al. 2022

Vaccine

View full text Add to dashboard Cite

“…Such Cellular Phylodynamic math could then be used to identify, rationally, the optimal dosages, schedules, composition, adjuvantation, pharmaceutical augmentation, and other aspects of vaccine implementation at single moments in time and in the presence of evolving variants. Since current methods for doing this are surprisingly empirical and superficial, 36 and for eradicating COVID-19, a failure, the possibility of developing a biologically sound, cell-number-based, Cellular Phylodynamic mathematics for optimizing COVID-19 vaccination would be appealing.…”

Section: Counting Cells May Help Us Get More Out Of Covid Vaccinesmentioning

confidence: 99%

Counting Cells by Age Tells Us About How, and Why, and When, We Grow, and Become Old and Ill

Citi

Huang

et al. 2023

Preprint

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Growth and aging are fundamental features of animal life. The march from fertilization to oblivion comes in enormous variety: days and hundreds of cells for nematodes, decades and trillions of cells for humans.1-4Since Verhulst (18385) proposed the Logistic Equation - exponential growth with a countervailing linear decline in rate – biologists have searched for ever better density-dependent growth equations,6-12none of which accurately capture the relationship between size and time for real animals.13-15Furthermore, while growth and aging run in parallel, whether the relationship is causal has yet to be determined. Similarly unknown has been the reason behind the exponentialForce of Mortality, described by Gompertz in 1825 for all-cause mortality16and reported by Levin et al. in 2020 for COVID-19.17Here we report that examination in units of numbers of cells,N, Cellular Phylodynamic Analysis,6reveals that growth, lifespan, and mortality, are linked to the reduction in the fraction of cells dividing, occurring by a simple expression, theUniversal Mitotic Fraction Equation. Lifespan is correlated with an age when fewer than one-in-a-thousand cells are dividing, quantifying the long-appreciated mechanism of aging, the failure of cells to be rejuvenated by dilution with new materials made and DNA repaired at mitosis.29-31These observations provide practical mathematical tools for comprehending and managing the challenges of growth and aging, for such tasks as deciphering COVID-19 lethality and its amelioration by vaccination.

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“…For all scenarios, the CoBe (Correlated Beta) DOA had similar or greater mean true utility relative to the other DOAs for all trial sizes (Figure 10, LHS). The mean true utility curve typically plateaued with between 30 and 60 trial participants for the single dose administration scenarios (1)(2)(3)(4), and between 60 and 90 trial participants for the prime/boost administration (5 and 6).…”

Section: True Efficacy/utility At Predicted Optimal Dosementioning

confidence: 99%

“…Dose can affect the efficacy, toxicity and cost associated with vaccine rollout [1][2][3]. However, selecting optimal dose ('dose optimisation') is non-trivial [4][5][6]. Vaccine dose-ranging trials are typically small (<100 individuals) [7][8][9][10], limiting the amount of data that can be used for dose decision making.…”

Section: Introductionmentioning

confidence: 99%

The Correlated Beta Dose Optimisation Approach: Optimal Vaccine Dosing Using Mathematical Modelling and Adaptive Trial Design

et al. 2022

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Mathematical modelling methods and adaptive trial design are likely to be effective for optimising vaccine dose but are not yet commonly used. This may be due to uncertainty with regard to the correct choice of parametric model for dose-efficacy or dose-toxicity. Non-parametric models have previously been suggested to be potentially useful in this situation. We propose a novel approach for locating optimal vaccine dose based on the non-parametric Continuous Correlated Beta Process model and adaptive trial design. We call this the ‘Correlated Beta’ or ‘CoBe’ dose optimisation approach. We evaluated the CoBe dose optimisation approach compared to other vaccine dose optimisation approaches using a simulation study. Despite using simpler assumptions than other modelling-based methods, we found that the CoBe dose optimisation approach was able to effectively locate the maximum efficacy dose for both single and prime/boost administration vaccines. The CoBe dose optimisation approach was also effective in finding a dose that maximises vaccine efficacy and minimises vaccine-related toxicity. Further, we found that these modelling methods can benefit from the inclusion of expert knowledge, which has been difficult for previous parametric modelling methods. This work further shows that using mathematical modelling and adaptive trial design is likely to be beneficial to locating optimal vaccine dose, ensuring maximum vaccine benefit and disease burden reduction, ultimately saving lives

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Could computer models be the key to better COVID vaccines?

Abstract: Past experience and best guesses won the day in the mad rush to beat back the pandemic. But dose-modelling tools might have made a difference. By Elie Dolgin Speed to approval and manufacturing capabilities factored in to dosing decisions for COVID-19 vaccines.

Cited by 4 publications

References 10 publications

Identifying COVID-19 optimal vaccine dose using mathematical immunostimulation/immunodynamic modelling

Identifying COVID-19 optimal vaccine dose using mathematical immunostimulation/immunodynamic modelling

Counting Cells by Age Tells Us About How, and Why, and When, We Grow, and Become Old and Ill

The Correlated Beta Dose Optimisation Approach: Optimal Vaccine Dosing Using Mathematical Modelling and Adaptive Trial Design

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