Trends of Business-to-Business Transactions to Develop Innovative Cancer Drugs
Round 1
Reviewer 1 Report
It is a well written manuscript that analysis the impact of inter-firm transactions on the development of cancer drugs. It provides a strategic suggestion and helps in understanding the trend in the business aspect of pharmaceutical industry.
Please see my comments below:
- In introduction, please clearly define 'success' -- does it mean approval rate, treatment results in patients, or profit the pharmaceutical companies make? I assume that authors consider 'approval rate' as a successful development, so what are the outcomes of treatment results and patients?
- In the Introduction, it is not statistically rigorous to state 'Therefore, we believe that sufficient data exist for a suitable sample size compared to other therapeutic areas.' The fact that sample size of cancer drugs exceeds that of other categories does not necessarily mean the sample size of cancer drug is suitable for a statistical analysis.
- In the Introduction, there is a statement 'Small molecules and biologics are often comparable in their...'. I assume the authors tried to say 'compared' because 'comparable' means 'similar', which does not logically fit the context and the follow contents.
- In Introduction, please provide more basic background information of PD-(L)1, Keytruda, Opdivo, and Tecentriq.
- The data is up to 2018, which is a little outdated. Please consider update it to at least end of 2019.
- Please elaborate the statistical analysis in Section 2.3. Such as the statistical analysis type, p-value or alpha value, the level of significance, etc.
- Please spell out the abbreviations in the figure captions and legends.
- In Figure 1, please label 'a' and 'b'. Also, it seems the caption and titles of Y-axis were swapped in the two figures.
- I would rephrase Hypothesis 1 because the results only indicate that there are more inter-firm activities for biologics, not necessarily indicate it REQUIRES inter-firm activities to develop biologics. The statement of Hypothesis 1 makes the inter-firm activity a prerequisite, which is not soundly supported by the results.
- Please label 'a' and 'b' in Table 1.
- I think the evidence is not robust and sufficient enough to make the statement 'This also implies that the number of transactions after the original approval in biologics generally exhibited a much more substantial increase than that of small molecules.'
- Please elaborate the meaning of the statistical symbols (maybe in both Section 2.3 and each figure's caption).
- In Figure 5, the Y-axis title is missing.
- For Figre 4 and 6, Please clarify in which R2 the correlation is considered statistically correlated.
- Please carefully revisit all the statements you make in Discussion and make sure they are logically robust.
Author Response
June 25, 2020
Dear Dr. Daniel Zhang, Assistant Editor
Re; Our responses to the reviewer’ comments
Sustainability_ 837868: An Econometric Analysis of Business-to-Business Transactions to Develop Innovative Cancer Drugs
Thank you so much for your e-mail letter informing the decision of major revision and referees’ positive suggestions on our manuscript. We highly appreciate you to give us an opportunity to improve our paper.
I am sending herewith a revised version of our manuscript. Also our point-by-point responses to the referees’ comments are described in the following pages (2-9).
We believe that we revised as their comments and we hope our responses meet their expectations and intentions.
We like to sincerely express our gratitude for your consideration. I look forward to hearing from you.
Warm Regards,
Arisa Djurian, MS, R.Ph, PMP
Graduate School of Technology Management, Ritsumeikan University
2-150, Iwakura-cho, Ibaraki, Osaka, 567-8570, Japan
+81-72-665-2100
Kota Kodama
Graduate School of Technology Management, Ritsumeikan University
Osaka, Japan
Email: [email protected] (K.K.)
Tel.: +82+72-665-2448
Author Response File: 
Author Response.pdf
Reviewer 2 Report
This paper investigates the effectiveness of inter-firm transactions during the discovery and development phases of oncology drugs, by evaluating the number of transactions and approval indications. The authors have conducted performed statistical analyses to study the trends of inter-firm transactions, the correlation between inter-firm transactions and approved indications, the correlation between inter-firm transactions and the number of approvals under BTD, and the trends in small molecules and biologics over the past 20 years.
Findings indicate the existence of a positive and significant correlation between the number of transactions and the average number of approved indications for biologics, but not for small molecules. It is revealed that the observed trend of active inter-firm transactions is key to increasing the probability of success in cancer drug research and development.
The concept of this study is interesting and if treated properly, it could add value at the relevant research. The main drawback of this paper is that too simple methodology is employed for the purposes of estimations. Correlations between variables should be replaced by modern methodologies such as dynamic correlations. Moreover, the authors should avoid presenting descriptive statistics as results, such as in Table 2.
It is my overall view that this study should be accepted for publication if and only if modern and more advanced estimation methodologies are adopted.
Author Response
June 25, 2020
Dear Reviewer 2
Re; Our responses to the reviewer’ comments
Sustainability_ 837868: An Econometric Analysis of Business-to-Business Transactions to Develop Innovative Cancer Drugs
Thank you so much for your e-mail letter informing the decision of major revision and referees’ positive suggestions on our manuscript. We highly appreciate you to give us an opportunity to improve our paper.
I am sending herewith a revised version of our manuscript. Also our point-by-point responses to the referees’ comments are described in the following pages (2-9).
We believe that we revised as their comments and we hope our responses meet their expectations and intentions.
We like to sincerely express our gratitude for your consideration. I look forward to hearing from you.
Warm Regards,
Arisa Djurian, MS, R.Ph, PMP
Graduate School of Technology Management, Ritsumeikan University
2-150, Iwakura-cho, Ibaraki, Osaka, 567-8570, Japan
+81-72-665-2100
Kota Kodama
Graduate School of Technology Management, Ritsumeikan University
Osaka, Japan
Email: [email protected] (K.K.)
Tel.: +82+72-665-2448
Author Response File: Author Response.pdf
Reviewer 3 Report
The title is misleading because it refers to “An Econometric Analysis of Business-to-Business transactions to develop Innovative Cancer Drugs” however no sound econometric methods are used. The analysis is based in very basic statistical methods: A t-test to test differences in means between two populations and a simple linear OLS regression performed in excel. Conclusions from simple regressions may be biased due to omitted control variables. The authors base their conclusions in the verification of the following hypothesis:
- Biologics require more inter-firm partnerships in their product life cycle than do small molecules.
- Inter-firm transactions positively impact the maximization of drug values, or specifically, the number of drug approvals.
The first hypothesis is tested by testing the difference in means of the number of inter-firm partnerships between biologics and small molecules drugs. This procedure allows to conclude that in average biologics have shown in the period under analysis more inter-firm partnerships than small molecules drugs. One has to know very well the pharmaceutical industry to speculate about the reason why this happens which the authors attribute to the fact that industry puts more open innovation in biologics. This may be true, but the statistical methods used cannot prove it.
The authors investigate Hypothesis 2 by comparing the number of approval indications between small molecules and biologics and performed a t-test to assess the differences in means. About this procedure, I am a bit worried if this result could be distorted by the fact that number of biologic and small molecules drugs are not be the same, that is if in the sample the number of biologic drugs is much higher than the number of small sample molecules than the probability that the first have more approval indications will be higher. Therefore, this difference would be due just to the difference in number of drugs analysed in each category. Nevertheless, this procedure does not allow to test hypothesis 2. The authors proceed by using simple linear OLS regression just to conclude that all biologics transaction categories statistically correlate with the number of approved indications but the same was not happen for small molecules. This statistical conclusion is not enough to prove hypothesis 2. For that a multivariate regression with the controls that explain the number of drug approvals would be needed. Also, the authors could give more details about the sample (like the number of drugs analysed in each year by category) and about the application of statistical methods used.
Minor comments:
Graphics in figure 1 seem to be exchanged according to the title
Author Response
June 25, 2020
Dear Reviewer 3
Re; Our responses to the reviewer’ comments
Sustainability_ 837868: An Econometric Analysis of Business-to-Business Transactions to Develop Innovative Cancer Drugs
Thank you so much for your e-mail letter informing the decision of major revision and referees’ positive suggestions on our manuscript. We highly appreciate you to give us an opportunity to improve our paper.
I am sending herewith a revised version of our manuscript. Also our point-by-point responses to the referees’ comments are described in the following pages (2-9).
We believe that we revised as their comments and we hope our responses meet their expectations and intentions.
We like to sincerely express our gratitude for your consideration. I look forward to hearing from you.
Warm Regards,
Arisa Djurian, MS, R.Ph, PMP
Graduate School of Technology Management, Ritsumeikan University
2-150, Iwakura-cho, Ibaraki, Osaka, 567-8570, Japan
+81-72-665-2100
Kota Kodama
Graduate School of Technology Management, Ritsumeikan University
Osaka, Japan
Email: [email protected] (K.K.)
Tel.: +82+72-665-2448
Author Response File: Author Response.pdf
Reviewer 4 Report
Usually, the Abstract should provide the following information - the scientific novelty; methodology of the research; originality; value; practical implications; limitations. Usually, exact numbers are not indicated in the abstract.
The aim, tasks, and methods used are not clearly identified neither in the Abstract nor in the Induction – needs some specifications.
Please check the first paragraph in “2.2. Variables and data sources”; the sentence on page 4, last paragraph “Figure 2 indicates that inter-firm transactions occur more actively occur with biologics than small molecules, and the …”. On page 9, the authors mention Figure 2, but the figure below this sentence is figure 6.
I missed the description of the used methods in chapter 2. Materials and Methods.
All figures and tables should cover in the description (title) the following – what, when, where, how (the measurement), and the source of data.
There are two figures 1, but in the text, they are named figure 1(a) and figure 1(b) – please correct —the same with tables Tables 1(a) and 1(b).
The description provided under Table 1 (last one) should be corrected – it is difficult to understand what the black lines mean.
Figure 4 should be mentioned (included) in the text and described appropriately.
I
am not sure that the publication will be colored, so think about colors in table 2.
The Conclusions and implications part could be extended with comprehensive information about the article, its basic idea, scientific importance, limitations, etc.
Please check whether al reference listed in the reference list are mentioned in the text (I missed reference “Makino, T.; Lim, Y.; Kodama, K. Strategic R&D transactions in personalized drug development. Drug Discov. Today 2018, 23, 1334–1339, doi:10.1016/j.drudis.2018.03.009.)
Please check the description of data sets, internet web pages – they should be accurately presented in the reference list.
Author Response
June 25, 2020
Dear Reviewer 4
Re; Our responses to the reviewer’ comments
Sustainability_ 837868: An Econometric Analysis of Business-to-Business Transactions to Develop Innovative Cancer Drugs
Thank you so much for your e-mail letter informing the decision of major revision and referees’ positive suggestions on our manuscript. We highly appreciate you to give us an opportunity to improve our paper.
I am sending herewith a revised version of our manuscript. Also our point-by-point responses to the referees’ comments are described in the following pages (2-9).
We believe that we revised as their comments and we hope our responses meet their expectations and intentions.
We like to sincerely express our gratitude for your consideration. I look forward to hearing from you.
Warm Regards,
Arisa Djurian, MS, R.Ph, PMP
Graduate School of Technology Management, Ritsumeikan University
2-150, Iwakura-cho, Ibaraki, Osaka, 567-8570, Japan
+81-72-665-2100
Kota Kodama
Graduate School of Technology Management, Ritsumeikan University
Osaka, Japan
Email: [email protected] (K.K.)
Tel.: +82+72-665-2448
Author Response File: Author Response.pdf
Round 2
Reviewer 3 Report
Thank you for your reply to my comments. I am clarified and satisfied with your arguments and corrections.
