Promoting Sustainability through Next-Generation Biologics Drug Development

Round 1

Reviewer 1 Report

The topic of the article is relevant to the readers of Sustainability, and relevant to the pharmaceutical industry.  However, in this reviewer's opinion this paper has a major gap on the application of the scientific method in publications that does not allow for an appropriate peer review of the work, since in some key places of the paper the methodologies used for the analysis are not clear, particularly in section 3.4 the methodology,  assumptions, data used for the analysis are not presented, thus one cannot perform an appropriate peer review to determine whether the conclusions of the analysis are sound based on the data, results, and limitations.

Specific recommendations are below:

• Section 1.4 - is this worldwide, or mostly developed world?  the current status of digitalization is varied depending on the location.
• Page 3, lines 98-100 - democratization of digital medical tools may be in process in the developed world, but not sure this can be generalized across the world without evidence that this is happening in remotes areas of countries without enough medical resources.
• 2.1.  In Materials and Methods the authors write "It is shown that data science and sustainability can improve productivity and depend
  152 on each other." This phrase is not describing a material or method, but the way it is written describes potentially a conclusion.  This needs to be either moved into conclusions or rephrased to show a material or a method.
• 2.2 I believe this section is unnecessary and my recommendation is to delete it and incorporate high-level definitions in the introduction.  The authors, for instance, have already defined and used on the paper most of the concepts described in this section (e.g., CMC, personalized medicine, digital twins, etc.  It is best for the reader to provide a short definition when these terms are first used instead of a full terminology section that distracts from the content.  Also note that 'digital twin' is not a new phrase in my opinion as it has been used in industry for many years, the first public reference I could find in a cursory search is about two decades old.
• 3.1  It may be easier for the reader to map the challenges here with some of the potential solutions that are described in 3.2-3.3
• 3.4.  The authors write "We have presented the impact of the (new) technologies and business practices on the achievement of the 10 SDGs in Table 2." The method to achieve to this qualitative assessment needs to be discussed, otherwise there is no opportunity to peer-review the contents of the table, or the reasons why 7 of the 17 goals have been excluded from the analysis.  This explanation could be added to the 'Materials and Methods' section in lieu of section 2.2.  For instance, the authors write that " Naturally, each technology has a different impact depending on the company and process, but a general calculation reveals that that future CMC departments act with more throughput while supporting sustainability goals."  The equation used by the authors to perform the general calculation needs to be shared along with any assumptions used so the results can be properly peer-reviewed.
• Page 16, lines 566-570.  The authors write "Technical, individual,
  nature, society, and democracy analysis (TING-D) is a tool for describing the value of a new product or technology in terms of the environment and society, the impact on democracy, and the values in terms of equality" - the authors do not seem to describe the methodology of the tool, or to provide an example on the results.  They describe that the TIN-G analysis "shows the impact on
  sustainability and the need for action" by looking at the following components:  technology, impact on individuals, impact on nature, impact on society, and democracy.  The authors described what it may seem like the output of the analysis, but since the methodology has not been described, not even shortly, it is not possible to appropriately peer review the claims without a description of the methodology, assumptions, and the evidence/data/facts used to derived the analysis.  For instance the authors write "Parameters like reducing resources to a minimum, the CO2 footprint, and a life cycle analysis like the Eco- care matrix can reveal the overall positive effects."  but do not provide any evidence that substantiates this claim.  
• A section on limitations, constraints, and challenges of adopting data science and related tools needs to be added.  This 
• A clear conclusion needs to be added describing the benefits, limitations, and a recommendation based on cost/benefit analysis.

Author Response

Reviewer1:

The topic of the article is relevant to the readers of Sustainability, and relevant to the pharmaceutical industry.  However, in this reviewer's opinion this paper has a major gap on the application of the scientific method in publications that does not allow for an appropriate peer review of the work, since in some key places of the paper the methodologies used for the analysis are not clear, particularly in section 3.4 the methodology,  assumptions, data used for the analysis are not presented, thus one cannot perform an appropriate peer review to determine whether the conclusions of the analysis are sound based on the data, results, and limitations.

Specific recommendations are below

• Section 1.4 - is this worldwide, or mostly developed world?  the current status of digitalization is varied depending on the location.

* We added a section to describe the use of digital apps and the production plants over the world in lines 114 - 128

• Page 3, lines 98-100 - democratization of digital medical tools may be in process in the developed world, but not sure this can be generalized across the world without evidence that this is happening in remotes areas of countries without enough medical resources.

*We added a section to describe the use of digital apps in lines 114

• 2.1.  In Materials and Methods the authors write "It is shown that data science and sustainability can improve productivity and depend
  152 on each other." This phrase is not describing a material or method, but the way it is written describes potentially a conclusion.  This needs to be either moved into conclusions or rephrased to show a material or a method.

* We deleted that sentence.

• 2.2 I believe this section is unnecessary and my recommendation is to delete it and incorporate high-level definitions in the introduction.  The authors, for instance, have already defined and used on the paper most of the concepts described in this section (e.g., CMC, personalized medicine, digital twins, etc.  It is best for the reader to provide a short definition when these terms are first used instead of a full terminology section that distracts from the content.  Also note that 'digital twin' is not a new phrase in my opinion as it has been used in industry for many years, the first public reference I could find in a cursory search is about two decades old.

* We discussed it and as the other reviewers did not ask for deleting the section and as we want to reach interdisciplinary scientists, we kept it.

• 3.1  It may be easier for the reader to map the challenges here with some of the potential solutions that are described in 3.2-3.3

* We mapped the solutions but left 3.2. to draw a complete image of a future laboratory.

• 3.4.  The authors write "We have presented the impact of the (new) technologies and business practices on the achievement of the 10 SDGs in Table 2." The method to achieve to this qualitative assessment needs to be discussed, otherwise there is no opportunity to peer-review the contents of the table, or the reasons why 7 of the 17 goals have been excluded from the analysis.  This explanation could be added to the 'Materials and Methods' section in lieu of section 2.2.  For instance, the authors write that " Naturally, each technology has a different impact depending on the company and process, but a general calculation reveals that that future CMC departments act with more throughput while supporting sustainability goals."  The equation used by the authors to perform the general calculation needs to be shared along with any assumptions used so the results can be properly peer-reviewed.

* We added a section in Methods and shortened the table.

• Page 16, lines 566-570.  The authors write "Technical, individual,
  nature, society, and democracy analysis (TING-D) is a tool for describing the value of a new product or technology in terms of the environment and society, the impact on democracy, and the values in terms of equality" - the authors do not seem to describe the methodology of the tool, or to provide an example on the results.  They describe that the TIN-G analysis "shows the impact on
  sustainability and the need for action" by looking at the following components:  technology, impact on individuals, impact on nature, impact on society, and democracy.  The authors described what it may seem like the output of the analysis, but since the methodology has not been described, not even shortly, it is not possible to appropriately peer review the claims without a description of the methodology, assumptions, and the evidence/data/facts used to derived the analysis.  For instance the authors write "Parameters like reducing resources to a minimum, the CO2 footprint, and a life cycle analysis like the Eco- care matrix can reveal the overall positive effects."  but do not provide any evidence that substantiates this claim.  

* We are in direct contact with the author André Baier and he suggested restructuring the figure, agreed to the final analysis, and added the tool to the Method section. We added his thesis as a source but also suggested him as a Co-author of this manuscript.

• A section on limitations, constraints, and challenges of adopting data science and related tools needs to be added. 

* We added section „2.3 Validating Machine Learning Models“.

• A clear conclusion needs to be added describing the benefits, limitations, and a recommendation based on cost/benefit analysis.

* We added a conclusion. 

Reviewer 2 Report

sustainability-1555969, Next-Generation Drug Development

The manuscript presented for evaluation fits to the journal’s scope and its quality standards. It is well documented and the information is presented correctly and attractively. Still, the overall tone of the paper is subjective in my opinion. The authors should be more objective presenting also the limitations and the problems associated with the “future drug development”.  The authors should discuss the drug development also in the context of the poor countries and their financial limitations.  The authors focus on Germany market and to some extent to UE and US. They should have a global view of the situation. It would be interesting to discuss the health problems of poor countries and the lack of interest of the pharmaceutical industry and how the authors consider that these issues will be address by the discussed new strategy.

In my view, the actual trend of the pharmaceutical industry is to focus on generic drugs rather than research on original ones (NMEs). It would be interesting for the authors to address also this issue and the repurposing strategies as alternatives.

The manuscript has editing mistakes. The authors should use the journal’s template and correct the editing accordingly.

Author Response

The manuscript presented for evaluation fits to the journal’s scope and its quality standards. It is well documented and the information is presented correctly and attractively. Still, the overall tone of the paper is subjective in my opinion. The authors should be more objective presenting also the limitations and the problems associated with the “future drug development”.  The authors should discuss the drug development also in the context of the poor countries and their financial limitations.  The authors focus on Germany market and to some extent to UE and US. They should have a global view of the situation. It would be interesting to discuss the health problems of poor countries and the lack of interest of the pharmaceutical industry and how the authors consider that these issues will be address by the discussed new strategy.

In my view, the actual trend of the pharmaceutical industry is to focus on generic drugs rather than research on original ones (NMEs). It would be interesting for the authors to address also this issue and the repurposing strategies as alternatives.

The manuscript has editing mistakes. The authors should use the journal’s template and correct the editing accordingly.

should discuss the drug development also in the context of the poor countries and their financial limitations.

* We added a section „1.3 Overall global challenges such as pandemics “ to the introduction and we took up the topic again in the conclusion.

Reviewer 3 Report

The manuscript sustainability-1555969 "Next-Generation Drug Development" by Katharina Paulick et al presents a summary of WHO's goals in next-generation drug development. 

The article is interesting, well written, and presents interest for "Sustainability" readers. 

As comments/suggestions:

In the context of the development of this next-generation drug, emphasis must also be placed on the human resource that must be specialized in future innovative fields. This implies a continuous and accentuated collaboration between the pharmaceutical industry (pharmaceutical laboratories), doctors, and universities in order to prepare future specialists in this field. What suggestions do you have for this?

Author Response

The manuscript sustainability-1555969 "Next-Generation Drug Development" by Katharina Paulick et al presents a summary of WHO's goals in next-generation drug development. 

The article is interesting, well written, and presents interest for "Sustainability" readers. 

As comments/suggestions:

In the context of the development of this next-generation drug, emphasis must also be placed on the human resource that must be specialized in future innovative fields. This implies a continuous and accentuated collaboration between the pharmaceutical industry (pharmaceutical laboratories), doctors, and universities in order to prepare future specialists in this field. What suggestions do you have for this?

* We added section „3.4 To cover the ever-increasing demand…“.

Reviewer 4 Report

In the review paper entitled „Next-Generation Drug Development”, the application of machine learning methods for green and sustainable drugs’ manufacturing and development was discussed based on the comprehensive and detailed literature overview. In general, the paper is well written, well-organised and the topic was discussed in detail. The authors presented various information which can be interesting for scientists and engineers dealing with sustainable and green technologies in the pharmaceutical industry. I have two suggestions listed below:

The authors should discuss the complexity of the models (architecture, learning algorithm, activation function functions, number of variables, etc.) and some other important technical issues such as overfitting, underfitting and overlearning problems.  

Lines 137-140: Please discuss this issue more in detail. Various interesting studies dealing with combining QSPR/QSAR methodology with machine learning appeared recently. Moreover, I suggest to mention about the original research works devoted to the application of artificial neural networks for developing green pharmaceutical methods (please see: DOI:10.3390/sym12122055; DOI: 10.3390/ma14205915; DOI: 10.1021/acs.jmedchem.9b02120; DOI: 10.5740/jaoacint.16-0203).

Author Response

In the review paper entitled „Next-Generation Drug Development”, the application of machine learning methods for green and sustainable drugs’ manufacturing and development was discussed based on the comprehensive and detailed literature overview. In general, the paper is well written, well-organised and the topic was discussed in detail. The authors presented various information which can be interesting for scientists and engineers dealing with sustainable and green technologies in the pharmaceutical industry. I have two suggestions listed below:

The authors should discuss the complexity of the models (architecture, learning algorithm, activation function functions, number of variables, etc.) and some other important technical issues such as overfitting, underfitting and overlearning problems. 

Lines 137-140: Please discuss this issue more in detail. Various interesting studies dealing with combining QSPR/QSAR methodology with machine learning appeared recently. Moreover, I suggest to mention about the original research works devoted to the application of artificial neural networks for developing green pharmaceutical methods (please see: DOI:10.3390/sym12122055; DOI: 10.3390/ma14205915; DOI: 10.1021/acs.jmedchem.9b02120; DOI: 10.5740/jaoacint.16-0203). 

* We added section „2.3 Validating Machine Learning Models“.

* We added section „3.1 Artificial neural networks are used for developing green pharmaceutical methods“.