[Vp-integration-subgroup] [Vp-reproduce-subgroup] Paper review and revision check list
Alexander Kulesza
alexander.kulesza at novadiscovery.com
Sun Jan 2 05:27:04 PST 2022
Dear all,
Happy new year to everyone. I hope that you are all well and safe and have
spent a nice holiday season.
I have tried to address
*Reviewer 2 *
*Moreover, when the authors mention ASME V&V40 procedure, it could be
useful to spend few words about the model credibility pipeline drawn for
predictive models in biomedicine, such as the one suggested in "Credibility
of in Silico Trial Technologies-A Theoretical Framing", Viceconti, M.,
Juarez, M.A., Curreli, C., ...Russo, G., Pappalardo, F., IEEE Journal of
Biomedical and Health Informatics, 2020, 24(1), pp. 4–13, 8884189.For this
specific aspect, the authors should talk about "specific question of
interest" and not "specific purpose" in the paragraph called "Credibility
of Models" to follow in such a way a standardised language.*
I have worked on the followng document in "track changes" mode:
https://docs.google.com/document/d/1IMEgmdNkx-EsnOjGuegpenSIMmKIkK00Lc8Gred3QxM/edit
Actually, I ended up in changing rather drastically the section. I think
that all ideas and all text is conserved, but I would very much like to
encourage you to read, comment and challenge this revision. Please tell me
if that goes to far. No problem to revert to an earlier version if
necessary.
I suggest the following formulation in the rebuttal letter:
When trying to better describe the "credibility pipeline" (CoU definition,
verification, validation, uncertainty quantification, e.g. as described in
Viceconti et al. 2019) or others, we noticed that the section about
credibility could be restructured in order to put the reader (not
necessarily familiar with regulatory assessment of models) in the position
to follow the argumentation.
We now roughly follow the following flow of writing:
- Every model needs a purpose and credibility is tied to that purpose as
well as repeatability and reproducibility
- Credibility is essential for models that have impact on regulated areas
or people's lives which is why regulatory authorities issue guidance
- The probably most advanced guidance ASME V&V40 suggests a risk-based
approach and pipeline to establish credibility of a model. It is
overarching and widely applicable
- Regulators and modelers work together (for example in frame of the model
informed drug development program MIDD) in order to better understand,
better apply and better uptake different kinds of models in regulatory
applications
- More work is needed to harmonize, stay up to date and to be more
inclusive
We hope that with the rather extensive change of the wording and additional
passages as well as citations (see below) we could address the concern of
reviewer 2 (and the general remarks of reviewer 1).
" In 2018 the American Society of Mechanical Engineers (ASME) issued an
important guidance ASME V&V 40 (ASME, 2018) of how to assess credibility of
computational models of medical devices through verification and validation
(V&V). The guideline is centered around the definition of the context of
use (CoU) of the model which is formulated based on the questions of
interest the model will answer. The CoU is then analyzed in terms of the
“model risk” - being the influence the model exerts on a decision and the
potential consequences these decisions might incur. Commensurate with this
model risk the modeler suggests establish the credibility goals, perform
verification validation and uncertainty quantification actions and then
assess the outcome of this exercise in order to allow judging the
acceptability of the model CoU. Key to this guidance is its overarching
nature which also allows adoption in other (e.g. drug development) fields
irrespective of the model type (Kuemmel 2020, Viceconti 2019)."
We also feel that it is essential to underline the cross-discipline
viewpoint of the ASME V&V40 which is further elaborated by the cited paper
by formalizing the verification, validation and uncertainty quantification
VVUQ pipeline across model types.
We therefore have added the following statement
" In the paper by (Viceconti 2019) the verification, validation and
uncertainty quantification (VVUQ) pipeline is streamlined to different
types of models. It is, perhaps, the closest to score credibility across
model types from mechanistic physics driven models to machine learning
models. However, it is still short of including very recent developments
such as ensemble models, although it touches upon the topic."
We additionally strengthened our argumentation by citing additional
literature
Bai, JPF, Earp, JC, Florian, J, et al. Quantitative systems pharmacology:
Landscape analysis of regulatory submissions to the US Food and Drug
Administration. CPT Pharmacometrics Syst Pharmacol. 2021; 10: 1479– 1484.
doi.org:10.1002/psp4.12709
FDA (2021b). Assessing the Credibility of Computational Modeling and
Simulation in Medical Device Submissions. FDA
Available at:
https://www.fda.gov/regulatory-information/search-fda-guidance-documents/assessing-credibility-computational-modeling-and-simulation-medical-device-submissions
[Accessed January 2, 2022]
Galluppi, G.R., Brar, S., Caro, L., Chen, Y., Frey, N., Grimm, H.P., Rudd,
D.J., Li, C.-C., Magee, M., Mukherjee, A., Nagao, L., Purohit, V.S., Roy,
A., Salem, A.H., Sinha, V., Suleiman, A.A., Taskar, K.S., Upreti, V.V.,
Weber, B. and Cook, J. (2021), Industrial Perspective on the Benefits
Realized From the FDA’s Model-Informed Drug Development Paired Meeting
Pilot Program. Clin Pharmacol Ther, 110: 1172-1175. doi:10.1002/cpt.2265
Kuemmel, C., Yang, Y., Zhang, X., Florian, J., Zhu, H., Tegenge, M., Huang,
S.-M., Wang, Y., Morrison, T. and Zineh, I. (2020), Consideration of a
Credibility Assessment Framework in Model-Informed Drug Development:
Potential Application to Physiologically-Based Pharmacokinetic Modeling and
Simulation. CPT Pharmacometrics Syst. Pharmacol., 9: 21-28. doi.org:10
.1002/psp4.12479
Musuamba, FT, Skottheim Rusten, I, Lesage, R, et al. Scientific and
regulatory evaluation of mechanistic in silico drug and disease models in
drug development: Building model credibility. CPT Pharmacometrics Syst
Pharmacol. 2021; 10: 804– 825. doi:10.1002/psp4.12669
Viceconti M, Emili L, Afshari P, et al. Possible Contexts of Use for In
Silico Trials Methodologies: A Consensus-Based Review. IEEE J Biomed Health
Inform. 2021;25(10):3977-3982. doi:10.1109/JBHI.2021.3090469
All the best
Alexander
On Sun, 19 Dec 2021 at 03:10, Jacob Barhak <jacob.barhak at gmail.com> wrote:
>
> Greetings to the paper contributors,
>
> You may have seen my other message where I posted the reviews to our
> paper. I am sending those again below to start a new thread discussing
> possible revisions.
>
> Here is a checklist for revisions required:
>
>
> 1. We should discuss the references that reviewer 1 raised and add
> them as reference
> 2. Reviewer 1 asked for more discussion around V&V40 - I believe Alex
> added the text there originally - Alex do you think you can address the
> request of the reviewer?
> 3. Reviewer 1 asked to focus on COVID-19 at the title - I am not sure
> we wish to limit our scope since many of our ideas are applicable far
> beyond COVID-19 - I leave it up for discussion in the group on how to
> address this request by the reviewer
> 4. Reviewer 1 asked for additional graphics - I am unsure how to
> address this beyond ur current diagram - ideas will help
> 5. We need to check the "Contribution to the field" section for
> grammar and spelling - if someone can contribute more elegant text - now is
> the time - I looked over it now and found no issues - yet I may have missed
> something - this section may have been missed since it was added last and
> perhaps vetted less than other sections. Also Reviewer 2 asked for grammar
> corrections, so it is worthwhile proof reading the paper as a whole.
> 6. Reviewer 2 asks for major rewrite to emphasize why the problems are
> there - I think we should explain that the core of the paper is the table
> and perhaps emphasize it in the paper beyond what the current text - we
> also should reply to the reviewer and explain that the paper is composed of
> contributions from a large group and we made an effort to include every
> voice in the choir - each of those voices is important and needs to be
> preserved - hopefully it will convince the reviewer that change we will add
> will be sufficient
> 7. Reviewer 2 asks to revise the introduction - I believe some
> changes are possible - yet the introduction includes contributions from
> many authors - at least 10 - and I fear losing something important someone
> contributed - if someone has an idea on how to address this reviewer
> without a painful transformation, please reply to this message.
> 8. Reviewer 2 wants additional discussion around the "reproducibility
> crisis" section and asks a valid question about expectations we should
> address - "“Computational biomedical modeling… was expected to be less
> affected by the reproducibility crisis.” Is this true, and why would it be
> so? " - My answer to the reviewer is that unlike biological processes that
> have random nature and experiments would not repeat if repeated, while
> computer software should be deterministic and it should be repeatable if
> designed well. Unfortunately we are not experiencing this promise - yet I
> believe the reviewer wants more discussion beyond this section so I am
> happy to discuss this.
> 9. Reviewer 2- writes: "Models are Hard to Locate: Are the authors
> suggesting that entire simulation workflows, from model construction to
> analysis, should be publicly available? At what point does one consider
> intellectual property? Do the authors advocate for such extensive
> publishing for all models, or only ones that are intended to be widely
> re-used? - those are important points we need to discuss - we need to
> better explain the difficulties we are having when creating models and the
> reviewer is absolutely correct about expanding the discussion to IP - I
> suggest we create a thread for this discussion and reference it - I
> suggest it we merged with the licensing issue that I will address later -
> there is a strong connection there - the reviewer was very observant and
> sees the bigger problem. However,we need to eventually distill our
> discussion to recommendations that will inline.
> 10. Reviewer 2 asks that we fix the unit standardization section - I
> believe Hana and myself were the largest contributors there - Hana - I will
> start a discussion on that topic in a separate email where we can publicly
> discuss how to fix this - others will be welcome to contribute.
> 11. Reviewer 2 asks that we better handle the section on Data
> availability and measurement definitions: in think we need to emphasize
> solutions and separate it from issues that may not be solvable. Ideas are
> welcome.
> 12. Reviewer 2 asks good questions with regards to licensing following
> our text- I personally have good answers to the reviewer and William and I
> had some discussion on the topic in this list I suggest we expand this
> discussion in a separate thread - hopefully William and perhaps others will
> join the discussion. This discussion should also address the IP issues
> raised by the reviewer for the "models are hard to locate section."
> 13. Reviewer 2 asks to handle the Model Application and Implementation
> Barriers section. We should decide what to do there, the section may need
> expansion since the ideas there are solid, yet the section is short so
> perhaps enhancing it makes better sense. I am open to suggestions.
>
>
> Those are the items I located and my suggestions. It seems we need
> attention from Alex, Hana, myself and william. However, anyone on the list
> is welcome to participate and suggest changes.
>
> I will start the discussion threads on specific topics. Hopefully we can
> get it done quickly.
>
> Jacob
>
>
>
>
>
>
> -
>
>
>
>
>
> ########### Original Reviews #############
>
> There are 2 reviews - both require major changes. I am copying the
> relevant text below. If more appear, I will let you know, yet I only got
> this message today although the reviews are dated a few days ago.
>
> Reviewer 1:
> Recommendation for the Editor: Substantial revision is required
>
> Please list your revision requests for the authors and provide your
> detailed comments, including highlighting limitations and strengths of the
> review. If you have additional comments based on Q2 and Q3 you can add them
> as well.
>
> Karr and co-authors made an interesting and exaustive point about the
> reproducibility crisis that leads to inability to reuse and integrate
> models, especially about COVID-19 disease.
> Within the manuscript some typos and missing information are present.
> I'd suggest the authors to revise the entire manuscript especially in
> terms of the state of the art, revising and updating the most relevant
> examples of computational models dealing with COVID-19 and in general about
> some semi-standardised proposals about the pipeline to follow for the
> verification and validation of model credibility. In particular, the
> authors failed to mention and cite some major results on in silico modeling
> about COVID-19 up to now. See for example:
> a."In silico trial to test COVID-19 candidate vaccines: a case study with
> UISS platform", Russo, G., Pennisi, M., Fichera, E., ...Viceconti, M.,
> Pappalardo, F., BMC Bioinformatics, 2020, 21, 527.
> b. Russo G, Di Salvatore V, Sgroi G, Parasiliti Palumbo GA, Reche PA,
> Pappalardo F. "A multi-step and multi-scale bioinformatic protocol to
> investigate potential SARS-CoV-2 vaccine targets" [published online ahead
> of print, 2021 Oct 5]. Brief Bioinform. 2021;bbab403.
> doi:10.1093/bib/bbab403.
> Moreover, when the authors mention ASME V&V40 procedure, it could be
> useful to spend few words about the model credibility pipeline drawn for
> predictive models in biomedicine, such as the one suggested in "Credibility
> of in Silico Trial Technologies-A Theoretical Framing", Viceconti, M.,
> Juarez, M.A., Curreli, C., ...Russo, G., Pappalardo, F., IEEE Journal of
> Biomedical and Health Informatics, 2020, 24(1), pp. 4–13, 8884189.
> For this specific aspect, the authors should talk about "specific question
> of interest" and not "specific purpose" in the paragraph called
> "Credibility of Models" to follow in such a way a standardised language.
> Moreover, the authors should refer to COVID-19 also in the title, with a
> specific mention about the fact that the main topic of model integration in
> computational biology will be discussed inside the COVID-19 context.
> Furthermore, for the model key concepts such as
> Reusability-Extensibility-Extractability-Portability the authors should
> described and outlined through a graphical sketch or visual representation
> that summarises these key point.
> The authors should also fix some grammar and writing typos present in the
> "Contribution to the field" section.
>
> a. Is the quality of the figures and tables satisfactory?
> - No
>
> b. Does the reference list cover the relevant literature adequately and in
> an unbiased manner?
> - No
>
> c. Does this manuscript refer only to published data? (unpublished or
> original data is not allowed for this article type)
> - Yes
>
> d. Does the review include a balanced, comprehensive, and critical view of
> the research area?
> - Yes
>
>
> Reviewer 2
>
> Please list your revision requests for the authors and provide your
> detailed comments, including highlighting limitations and strengths of the
> review. If you have additional comments based on Q2 and Q3 you can add them
> as well.
>
>
> The article often reads as a stream-of-consciousness account of the
> discussions that took place but lacks a clear thesis or recommendations. It
> is not clear what, if anything, the authors are advocating for. It is not
> always clear why the issues being discussed are problematic, or that they
> can be reasonably addressed. Some of the issues raised are indeed important
> and should be discussed, but the paper lacks focus and does not tell a
> cohesive story. I believe this manuscript requires a major re-write to be
> suitable for publication. The authors should consider narrowing the scope
> of the discussion and focusing on a cohesive set of recommendations or open
> questions. More specifically, I make a few suggestions below:
>
> Major comments
> 1. The introduction is long and repeats itself (e.g., “much less is known
> about how viral infections spread throughout the body…” is repeated
> verbatim). It is not clear from the introduction what the main goal of the
> paper is or why the “reproducibility crisis” is truly a crisis. Why is the
> discussion of composition and black/white box models relevant to the
> introduction? Further, this section is subtitled “the promise of modeling”,
> which does not seem to match the content.
> 2. The Reproducibility Crisis: “Computational biomedical modeling… was
> expected to be less affected by the reproducibility crisis.” Is this true,
> and why would it be so? One would think that more complex models would
> suffer more from a lack of reproducibility. It may be helpful to define
> what exactly the “reproducibility crisis” refers to.
> 3. Models are Hard to Locate: Are the authors suggesting that entire
> simulation workflows, from model construction to analysis, should be
> publicly available? At what point does one consider intellectual property?
> Do the authors advocate for such extensive publishing for all models, or
> only ones that are intended to be widely re-used?
> 4. Unit standardization: The conversion from PFU or TCID50 to individual
> virions is likely to differ across viruses – are the authors focused on
> COVID here? Are the authors advocating for a standard conversion factor? It
> is not clear what the purpose of this discussion is. As the authors
> mention, different scales require different units. Even at a single scale,
> different models may require different units for numerical reasons. It is
> not clear what the authors are advocating for here.
> 5. Data availability and measurement definitions: This section seems to
> outline limitations of available data, but again makes no recommendations
> or proposed solution to any of the issues raised. Is this the intention?
> Most of the issues raised here reflect limitations of experimental science
> or data privacy, which likely cannot be meaningfully addressed by the
> modeling community.
> 6. Models are Not Consistently Licensed…: Are the authors implying here
> that all modeling work should be published with no rights reserved? Is it
> reasonable to expect modelers to make their work freely usable by others
> for profit? Is it reasonable for institutions to allow this? How much does
> this really contribute to reproducibility and utility?
> 7. Model Application and Implementation Barriers: This section seems
> unnecessary and out of place.
> 8. There are grammar and punctuation errors scattered throughout; please
> edit carefully.
>
>
> a. Is the quality of the figures and tables satisfactory?
> - Not Applicable
>
> b. Does the reference list cover the relevant literature adequately and in
> an unbiased manner?
> - Yes
>
> c. Does this manuscript refer only to published data? (unpublished or
> original data is not allowed for this article type)
> - Yes
>
> d. Does the review include a balanced, comprehensive, and critical view of
> the research area?
> No answer given.
>
>
> ========
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--
Alexander Kulesza
Team leader
Modeling & simulation / Biomodeling
alexander.kulesza at novadiscovery.com
+33 7 82 92 44 62
nova
DISCOVERY
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