An exclusive interview with Genewiz China general manager Ethan Ge
Since the new millennium bell chimed, we have seen great changes brought by Internet. Big data technology and artificial intelligence (AI) have made breakthroughs in recent years and have been reshaping our life from every aspect, from the mode of travel, communication channel, consumption habits to daily life. On the other hand, our traditional recognition to health management, disease prevention and treatment are subverted from time to time by new knowledge of life science ushered in by genomics. What is the theme of the times, information technology or biological technology? Ethan Ge, general manager of Genewiz China, a versatile talent with dual educational background of both computer and life science, likes to compare God to a great programmer using AGCT quaternary code to decipher secrets of life. In his opinion, BT and IT represent two technological directions, like the two pieces of gong, only by colliding with each other can they play beautiful movement of the 21st century.
Ethan Ge, general manager of Genewiz China, global CIO of Genewiz, bachelor and master in Biomedical Engineering and Instrumentation from Tsinghua University, MS in bioengineering from University of Tennessee, and MBA from Rutgers University. He has focused on the biomedical engineering and has nearly 30 years of experience in scientific research and management in the biomedical software development, AI system, biological information technology, and cloud computing. After joining Genewiz in 2014, he has headed Genewiz’s IT team to complete the CLIMS 4.0 online order and laboratory process management system, published the industry’s first genomics mobile service APP, which makes intelligent and informatization reconstruction to the processing of genomic service outsourcing projects. This move significantly improves researchers’ order management and laboratory efficiency.
1.Hello Mr. Ge, how do you think about the development and relationship between life science and information science as an interdisciplinary talent with rich experiences in both fields?
Life is a complicated phenomenon. Life science has a difficulty that it is hard to quantify or express in a precise mathematical model or algorithm. In the post-human genome era, we have made many breakthroughs in the understanding of life, but some problems we faced 30 years ago are still posing challenges. Or this can be described as “co-existence of opportunities and challenges”.
I enrolled in Tsinghua University in 1988, majored in biomedical engineering and instrumentation and has worked centering on IT and life science in the past 30 years. These two disciplines are exciting and many breakthroughs have been made in these fields.
In 1999 I served PHYSIOME SCIENCES in New Jersey, the United States. My main research was to model the biological pathways, pharmacodynamics and effects of medicine on organism. At that time the company spent US$5 million buying the latest Unix server -IBM eServer p690 (Regatta). Though there was not the concept of big data, we actually did the so-called big data works - collecting massive experimental data and literature reports to summarize mathematical models, and then using the models to predict effect of the drugs on organism.
We made some achievements, but there were questions whether such models could replace the laboratory experiments and whether such results were recognized by biologists. Today computer performance has been substantially improved, but we face the same questions on how to precisely predict reaction of organism on drugs or the biological pathways.
Last year I attended BI-IT World in the United States and saw some of the latest models and algorithms, and significant improvement in performance. However, they still could not replace animal experiments and clinical trials. Generally, I think mature models still need to combine theories with practice, and guide directions and assumptions with the mathematical models and verify the assumptions with experiments, just like what Genewiz has done to assist customers to develop antibody drug with our genomics and bioinformatics services.
As for relationship between the two disciplines, IT has been serving life science ever since, whether in our gene data analysis or medical image pattern identification. Take Genewiz for example. We have equipped and pooled advanced IT resources to serve research fellows of the life science field, from intelligent and IT-based order management system to biological information analysis platform with high-performance computing and cloud storage. These advanced IT technologies help researchers accelerate project progress. In return, discovery and application needs of life science significantly enhanced development of the information technology. For example, artificial neural network and genetic algorithm are actually conceived from the brain structure and the natural phenomena of biological inheritance.
2.Gordon Moore, founder of Intel, set forth the renowned Moore’s Law which describes the rapid development of computer. Today the genome sequencing is said to outpace Moore’s Law. What do you think they have in common?
What we expect is the effect brought by Moore’s Law. It is because microprocessor has developed rapidly as predicted by the law, making PC a household goods, generating a large number of applications and bringing opportunities for the computing technology industry to take off. As for the More-Than Moore’s Law in genome sequencing, we hope to generate more applications with development of sequencing technology.
Just like when PC entered home, people were not clear how to use it except for playing games. Today our daily working and life cannot be separated from PC which has gotten involved in all aspects of our life from working, study, shopping, entertainment to children education. Actually today’s many business modes and services on mobile Internet are scenario extension of smartphone-based applications. Then what new applications can genome sequencing have in scientific research? Is there any similar noninvasive prenatal testing application? In addition to identifying our ancestor, does it have more useful scenarios?
In my opinions, there will be more applications in the food and health fields. Today we can identify whether the salmon is authentic with the genome sequencing technology. With lowering sequencing costs, can we apply the technology in the conventional food and fruit testing in the next step? In research we have started to assess intestinal health and disease progression by analyzing the gastrointestinal microbiota. Can we use it to guide our personal dietary habits in future? This probably requires to draw on the wisdom of the masses to jointly create and promote application development. As a global genomics service provider, Genewiz is looking for more applications of genome sequencing by cooperating with global partners.
3.The reduction of sequencing costs enables wide application of genome sequencing technology. The following issue is how to handle and analyze massive biological data. As Genewiz’s global CIO, how do you think about it?
Gene data naturally has the attributes of big data. Each sequencing will produce a large amount of genome sequencing information. The reduction of sequencing costs provide great convenience for researchers to understand and study life from the perspective of gene sequence.
Of course data itself cannot generate knowledge. Only with effectively processing, analyzing and mining can the value of data be tapped. In my opinion, the key of data processing is to eliminate the false and retain the true and realize sample to answer - whether sample analysis can answer the question under study.
Considering the complexity of life phenomena, the gene data can hardly clearly explain all research questions. Many studies have started to analyze clinical representation and gene data in combination so as to get an accurate picture of the human disease and health from a more complete angle. This is an opportunity brought by development of genomics and big data analysis, and challenge as well. The biggest problem lies in the medical data sharing. How to form a complete planning? How to standardize the sample data? How to solve data sharing security and legal concerns among hospitals?
Compared to the gene data with unified standards, clinical information and information recording are lack of certain norms and standards, and show low level of digitization and differentiated language expression, causing difficulties in use of such information. At the current stage, one of the most important tasks we need to do is probably to formulate an acceptable standard to unify the medical information from different sources. Some governments and industrial associations have started to solve this problem, and initiated establishment of standards and regulations to set up a shared biological sample base. Relying on Nanjing Yangtze Technology Innovation Platform, Genewiz has participated in the national medical big data sequencing and mining program. We are looking forward to working with scientists to interpret secrets of life and promote treatment of diseases in future.
4.In your opinion, what changes can be expected in the research fields of the future life science brought by currently booming AI technology?
Just like what we mentioned before in the analysis of biological big data, combining gene data with medical information will lead to development important applications and AI technology. I have touched many basic theories in the AI field in the 1980s when I studied in Tsinghua University. It was called pattern recognition which could help process some simple issues. Today’s many AI theories are similar to what I learned at Tsinghua University, with seemingly only more layers in the neural network. It seemed no major changes happened in the sector. But today the enormous data resources and superior computer performance, in addition to algorithm optimization, jointly provide unprecedented capability for AI, for example AlphaGo which defeated a human Go player.
In the life science field, whether breakthroughs can be made in studies is highly associated with the research direction because of complexity of life phenomena. At present Genewiz has started to make some efforts, for example codon optimization in the field of gene synthesis, target screening in antibody drug development, gRNA design in the field of gene editing and the like can use AI algorithms to help researchers find the best answers and improve their research efficiency.
In future, with continuous optimization of gene technology and AI algorithm, customized life design can be realized technologically. Compared with today’s early teaching and training, establishing skill advantages in all aspects by optimizing gene is more tempting for many parents. Such scenarios in science fictions in the past are likely to change human in the future, though there are many ethical problems.
5.As a global genomics service provider, Genewiz has released the online ordering system and mobile terminal, and taken a lead in digitization and information platform construction in the industry. What will Genewiz bring to the genomics service field in the future?
Each company should address some social development requirements and issues. For Genewiz, it is our mission to lower costs of researchers by providing them with high efficient and high quality services. We have made efforts centering on efficiency and quality, for example introducing the most advanced high throughput sequencing platforms HiSeq X Ten, NovaSeq and PacBio Sequel, releasing intelligent online ordering system, and mobile terminal order management published recently. By introducing Industry 4.0 from Germany, we have made intelligent renovation of the experiment process. This move has substantially improved the order processing efficiency and quality, and provided customers with many other conveniences from placing order to receiving results.
Though technological instruments and research focuses are changing, researchers’ requirements on time and quality will remain unchanged, in my opinion. Genewiz runs 15 genomics labs in several countries across the world, and provides research services for hundred of thousand researchers, including 30 Nobel laureates. In the future, we will establish one-stop life science service platforms relying on the huge customer base, in addition to continuously consolidating our service capability in the genomics field. We hope to cooperate with high-quality manufacturers to expand businesses in proteomics and metabonomics, in addition to the genomics services, so as to jointly provide comprehensive services to researchers in the life science field.
We will continuously blaze new trials in a pioneering spirit in the fields of AI and big data analysis, and provide more precise gene analysis and better gene synthesis services to scientific research personnel with our CLIMS 4 cloud platform in a more efficient way.
New Year’s message
I was attracted to this industry by the description that time. Today I am more confident that the 21st century is the century of life science. In the past 18 years, Genewiz luckily witnessed important breakthroughs and progresses in the life science sector. From Sanger sequencing to G2 and G3 sequencing services, the sequencing technology has helped scientists across the world to interpret secrets of life. From H7N9 virus, the Ebola virus to the Zika virus, we have worked with researchers of the health field and doctors to crack the virus spread mechanism to gain the initiative. From the world's first human mitochondrial genome, chloroplast genome to the Saccharomyces cerevisiae genome synthesis, we are marching forward hand in hand on the path of deciphering the secrets of life.
In 2018 Genewiz is willing to work with colleagues in the life science field to help all customers to march to the next breakthrough and next discovery with out improved high-efficient and high-quality services!