The flagship of our Human Practices efforts this year is the development of the OSIRIS (Optimized Societal Impact & Risk Integration System) Protocol; a methodology to efficiently receive and quantitatively integrate feedback into any synthetic biology project.
Any project, any initiative, however structured and well designed, will require feedback and through its fruition, adjustments will be made. Our team, upon deciding on its project and planning the basic steps to follow, had to try and find the most relevant researchers and professors in the field. Its purpose, of course, was to consider their opinions and utilize them to tweak various parts of our project accordingly. Despite our efforts, we could not pinpoint someone in Greece that was an expert regarding our topic, thus we had to extend our reach worldwide. While trying to get in touch with researchers from all over the world and participating in the 4th Systems and Synthetic Biology Summer School, we thought of decomposing the whole process that we've been through, in short, individual steps. We, then, had the idea to search vast-scale opinion taking from people of interest in world-wide range. We stumbled upon Societal Risk Evaluation Scheme (SRES), developed by Cummings & Kuzma et al., 2017 [1], that identifies and evaluates risks regarding Synthetic Biology projects. As it did not perfectly fit our case, we decided to modify specific parts of it, so that if will not only find possible risks regarding our project, but will also aid us in finding ways to mitigate them. However, as it requires experts to provide their feedback on various concerns, we fed it with the results of our primary eSWOT Analysis and different versions of Stakeholder Maps. Combining all those steps, the creation of OSIRIS became a reality. For an analytical, step-by-step explanation of the protocol, click here.
1.We've carried out an eSWOT Analysis. eSWOT is an enhanced SWOT analysis in order to evaluate Strengths, Weaknesses, Opportunities, and Threats (SWOT) of our project.
So it is said that if you know your enemies and know yourself, you can win a hundred battles without a single loss. If you only know yourself, but not your opponent, you may win or may lose. If you know neither yourself nor your enemy, you will always endanger yourself.-The Art of War by Sun Tzu
In order to holistically evaluate our idea in the context of the real world, we explored the process of identifying favorable and unfavorable factors during the SWOT analysis after examining the findings of the Helms & Nixon., 2010 [2]. We employed a brainstorming method of our own invention termed PCR (Parameter Chain Reduction) analysis in order to feed validated-only SWOTs in the final analysis. Our PCR includes the following steps:
- (1) Possible SWOTs are proposed through team discussions.
- (2) SWOT candidates are decomposed into simplified complementary statements.
- (3) Socratic method (also known as maieutics, method of elenchus) is utilized as a way to thoroughly investigate possible strengths, weaknesses, opportunities and threats. The team is divided into groups of two interlocutors, one that asserts the proposed SWOT statement and one that targets for refutation.
- (4) Only SWOT candidates that survive the in-depth debating (during multiple rounds) are tampulated in the final eSWOT analysis.
eSWOT Analysis helped us realise the opportunities of our idea and inspired us on finding other future applications of pANDORRA.
2. We've created a Stakeholder/Value Matrix to identify all stakeholders that might have interests or concerns regarding the proposed project. We've obtained our first look of a sample of multidisciplinary experts who can provide greater insight into detected or emerging project issues.
Stakeholder/Value Matrix worked as another reminder of how important biosafety and the safety of patients is. Therefore, we worked even harder to chisel a project with as many safety checkpoints as possible.
3. We've created a Stakeholder (Expert) Map in order to map the stakeholders (experts) according to power and interests.
From the data analysis of Stakeholder Map we were able to pinpoint the stakeholders we should contact to transform our project's features in the best possible way. As signified by their high power to influence our project and interest, the aforementioned stakeholders-experts we contacted are mostly Researchers, University Professors and Clinical Doctors.
4. Finally, we've created a Risk Map to better understand the risks of the project in order to define areas of improvement in our method. You can find our risk map here.
The Risk Map showed us the areas on which we could improve our project. These are the possibility of false prediction of miRNA candidates for our classifier circuits based on conventional bioinformatic methods and the concern about a possible environmental ecosystems disruption. We moved towards the mitigation of such problems through extensive modeling of our classifier and by establishing several levels of safety. We also propose that a future treatment should be carried out in a controlled environment under the supervision of highly-trained clinicians.
After a thorough examination of the literature, we've concluded that current methods of evaluation and reshaping of synthetic biology projects according to the stakeholders' feedback are limited and face the following problems:
- -Socioeconomic and ethical issues are often dismissed [3,4]
- -Upstream public engagement, often a proposed tool for integration of users' opinion in the design, is impaired by the complexity of synthetic biology as a whole [5]
- -Multi-criteria analyses using stakeholders' judgement to assess an idea are not causally connected to the integration of this feedback in the technical, safety, ethical, societal aspects of a project [6]
Inspired by the work of Cummings & Kuzma et al., 2017 [1], we have developed a new methodological contribution to the field, termed OSIRIS (Optimized Societal Impact & Risk Integration System). OSIRIS constitutes a robust system that is capable of outlining risk factors and concerns in various fields and sectors, by analyzing qualitative and quantitative data from a multidisciplinary panel of experts with diverse perspectives and affiliations. The OSIRIS can assess, but is not limited to, the following factors:
- -Health risks
- -Health benefits
- -Environmental risks
- -Uncertainty
- -Risk Manageability
- -Commercialization potential
- -Public concern
- -Ethical dilemmas
It is a tool aimed to enhance risk governance by summarizing predicting risks and it is expanded in order to evaluate risk manageability and provide optimal solutions. We consider it a significant boost for iGEM teams to investigate and manage risks and safety parameters in a quantitative way and a robust screening tool to prioritize information collection, hazards identification and expert's opinion integration to the workflow of synthetic biology innovations.
OSIRIS consists of a tweaked 3-round Policy Delphi method. Named after the Oracle of Delphi, it is a forecasting, decision support method that uses the panel of experts to distil responses and build toward group consensus regarding the risk prediction of the proposed project. The panel of experts was pre-selected by the pre-analysis results of our Stakeholders (Experts) Map. Our modified Policy Delphi works as follows (3 Rounds):
- Open-ended interviews in the form of Q&A for qualitative data collection regarding general issues of our project (via email, Skype, in-person interview).
- Formation of quantitative online survey after evaluating the answers of the 1st Round. This Round is comprised of 8 sets of questions (each set has 2 categories: Risk/Benefit, Uncertainty).
- During Round 3, after analyzing the concerns that have arised from Rounds 1 & 2, we performed a short-round of questioning, internally between team members and externally with our advisors and synthetic biology experts in conferences. This round was designed in order to simulate the challenge for iGEM teams to come-up with radical redesigns for their project according to the received feedback.
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- 28 answers in our Round 1 open-ended questionnaire out of which 7 were from PIs/Instructors of iGEM Teams, 9 researchers in Greece and 12 postdoctoral researchers and professors in Europe, Asia and America.
- 66 answers in our Round 2 quantitative questionnaire out of which 46 were from experts such as PIs/Instructors from other iGEM Teams and 20 were from experts that we managed to pinpoint around the globe.
- Outreach to more than 80 Ambassadors, called Muses, from countries on every continent, from which more than 60 were actively engaged in promoting Synthetic Biology and identifying experts in their respective fields.
* Osiris first recruited the nine Muses, while embarking on a tour of all Asia and Europe, teaching the arts of cultivation wherever he went.
Each SB application is summarized using an additive risk/benefit and certainty index and ultimately a mean risk/benefit and certainty score.
In case of Risk(R):
\[R = (\sum\limits_{i = 1} {{r_i})/n} \]Our results are visualized in octagonal plots that allow for granular assessment of each factor of the OSIRIS protocol in terms of both its risk or benefit profile as well as expert uncertainty of current understanding of that given criterion and its potential management.
After the visualization process and after the completion of Round 3, we can say we have a better understanding of probable mishaps that can happen with our design, as estimated by the scientific and clinical community. Moreover, we have a better view of our design's strengths. We made the following observations and took specific actions:
1. Great public concern might be generated due to the use of genetically engineered E. coli, with a more than average level of certainty as indicated by the experts' answers. That's why we created a visual lingua franca to communicate our integrated design to the greater public, independently of the various social groups' interest and educational level.Check out BUILDING A VISUAL LINGUA FRANCA TO REACH OUT TO THE WORLD.
2. There is a strong basis that supports the beneficial nature of RNAi-classifiers to human health applications, like cancer therapeutics. However, we want to further explore this potential, by tackling technical complexities and creating pANDORRA, an open-source toolkit with basic Parts to build various multi-layered cell-type classifiers.
3. We noticed that there is a blurred line regarding the applicability of anticancer E. coli, however there seems to be a group consensus regarding their health and environmental risks. To tackle this widely spread issue we put great care into developing a therapeutic approach with serial fail-safes. Moreover, the last fail-safe, the inclusion of the cancer selective toxin named Apoptin was added after discussing with Prof. JD Keasling about the therapeutic efficacy of complex engineered circuits. Check our system here.
In this journey, we also had the chance to have in-depth discussions with other various experts, who kindly provided us with technical feedback which we developed in different iterations of our project.
1. Laboratory of Systems and Synthetic Biology, University of Wageningen
Stamatis is a PhD candidate in Laboratory of Systems and Synthetic Biology of Wageningen University under the supervision of Prof.dr.ir. VAP (Vitor) Martins dos Santos. In order to create a modular system that can be compatible with various assembly platforms, we've contacted Stamatis who has extensive experience on the expansion of current tools for chassis and circuit engineering. He was extremely helpful and eager to collaborate with us. We had an exciting back-and-forth interaction where he argued about the compartmentalization of the building blocks of circuits in synthetic biology, even in complex systems like mammalian cells. That completely changed the direction of our initial approach. He proposed the use of the customizable vectors where any researcher can insert different binding sites for preferred miRNAs in the 3' untranslated region of specific genes. It has been a blast and one of our most exciting moments in iGEM integrating his feedback and coming up with solutions to increase the modularity of our system.
1. Max Planck Institute for Molecular Genetics (IMPRS-CBSC), Berlin, Germany
2. Freie Universität at Berlin, Department of Mathematics and Computer Science, Berlin, Germany
While attending the 4th International Synthetic & Systems Biology, during the poster session, we met with Melania who was presenting a poster regarding the design of optimal cell-type classifiers. She was really kind and energetic during our discussions as she thoroughly informed us about the significant benefits of computational design of logic circuits with miRNA molecular switches. After our conversations, we quickly reshaped our computational modelling, developing a new classifier optimization tool that can dictate the architecture and logical expressions used in the wet lab.
Our project acted as a proof-of-principle for OSIRIS, proving that OSIRIS is a multi-faceted tool that can be employed for a wide range of synthetic biology projects developed by a research group (iGEM-related or not) in order to evaluate potential risks and benefits in multiple fields and incorporate in a systematic manner, opinions by a multidisciplinary panel of experts and stakeholders.
- [1] Cummings, C. L., & Kuzma, J. (2017). Societal Risk Evaluation Scheme (SRES): scenario-based multi-criteria evaluation of synthetic biology applications. PloS one, 12(1), e0168564.
- [2] Helms, M. M., & Nixon, J. (2010). Exploring SWOT analysis–where are we now? A review of academic research from the last decade. Journal of strategy and management, 3(3), 215-251.
- [3] Thompson, P. B., Kassem, M., & Werner, W. G. (2007). Food biotechnology in ethical perspective.
- [4] Paradise, J., Wolf, S. M., Kuzma, J., Kuzhabekova, A., Tisdale, A. W., Kokkoli, E., & Ramachandran, G. (2009). Developing US oversight strategies for nanobiotechnology: learning from past oversight experiences.
- [5] Wilsdon, J., & Willis, R. (2004). See-through science: Why public engagement needs to move upstream. Demos.
- [6] Malloy, T., Trump, B. D., & Linkov, I. (2016). Risk-based and prevention-based governance for emerging materials.
