Victor Joo Chuan Tong blends computer science and biology in his research.

esearcher Victor Joo Chuan Tong, selected this year as one of the world's top 35 young innovators in science and technology by Technology Review magazine, was born, bred and trained in Singapore. Having gained an undergraduate degree in computer science, he moved into bioinformatics and now works at the A*STAR Institute for Infocomm Research. Here he tells INNOVATION about the research that won him the award.

You were named a young innovator by Technology Review for your vision of personalized vaccines. What is this vision?

Tong: Vaccines have been around for about 200 years, since an Englishman named Edward Jenner started using cowpox to vaccinate against smallpox, but we still have problems with vaccine design. I am interested in routes to find new safe and effective vaccines.

The traditional methods of vaccination, such as using live, attenuated or dead pathogens, can have side effects and may carry risks. For example, an attenuated vaccine may undergo a secondary mutation and then become infectious again. The newer generations of vaccines are known as subunit vaccines, and these are based on fragments of the pathogen that stimulate an immune response. We call these subunits antigens.

But all of us have different immune responses. We each have different versions of the proteins, called human leukocyte antigens (HLAs), that recognize antigens of bacteria, viruses and other microorganisms. Your cocktail of HLAs and my cocktail of HLAs may be different. As such, your immune system might recognize different fragments of a pathogen as compared to mine. My research involves trying to use advanced algorithms — a software approach — to predict which fragments of a pathogen are likely to activate a strong immune response, taking into account individual genetic variation in HLAs. These fragments are candidates for developing subunit vaccines.

How did you end up working on vaccines when you did a degree in computer science?

Tong: When I was very young I loved biology, and it was only as I got older that somehow I moved to computers — probably I was playing too many games! When I graduated from the National University of Singapore (NUS) computer science program around 2002, Singapore was promoting life science research. I saw an opportunity and decided to switch to bioinformatics.

At the time I joined the NUS Department of Biochemistry, we were trying to find some cure or prevention strategy for SARS. I came to appreciate that vaccination is a very good form of public health intervention and that there's a need for better ways to design more effective vaccines. I have worked on a few other projects at the time, but this one is very meaningful in a local context because there are so many viruses emerging.

How much difference would personalization make to a vaccine's efficacy?

Tong: To give an example, the flu shot is only 40% effective for this year's (2008) flu viruses. This means that either the viruses used in the vaccines are not similar to those in circulation or the vaccine recipients do not possess the relevant immune profile to recognize the particular antigens used in the vaccine.

So would you need to design an individual vaccine for each person?

Tong: This would depend on our strategy. We could decide to design a broad-based vaccine or, for example, aim for a populationspecific vaccine, maybe for Singaporean Chinese or Singaporean Malays. We know that different populations have different HLA profiles. In Europe, for example, one finds predominantly HLAA1s, while in North America and Asia, HLA-A2 is more common. HLAs in Singapore, because it is a multiracial society, are quite diverse.

An individually customized vaccine would be the extreme case, and may be suitable for the prevention or treatment of cancer. In principle, to design an individual vaccine, I would just need information about your immune profile, i.e., your HLAs, and then I can identify based on our algorithms how your immune system would identify the particular virus. Your HLA types could even be included in your medical record. Cost will be a consideration here; of course a broad-based vaccine is less expensive than a personalized one.

How, in detail, does your prediction software work?

Tong: We are using 3D models of the different HLAs to predict how strongly different candidate antigens will bind to them (see Fig. 1). The binding step will tell us how well the HLA may "recognize" the fragment. The typical length of an antigen that can bind to an HLA is 7 to 14 amino acids, so it is only a small fragment of the pathogen. Once we have identified the highest potential antigenic regions of the pathogen, we tell our experimental collaborators. They can then test the antigens in cells or animals. The most important step in vaccine or drug discovery is target identification, and a software-based approach could help significantly reduce the amount of time needed.

There are a few groups trying to design personalized vaccines in a similar way, but our approach is technically different. Our focus is on the use of 3D models of the HLAs, others are just using sequences.

You have described the theoretical side of the work. What success has there been in the lab?

Tong: We are currently at an early stage. We started developing an integrated vaccine discovery pipeline about one year ago, and the wet part takes some time. When we compare our results with data already in the literature, we find that our models can achieve up to 96% accuracy in predicting binding. Our collaborators in the wet lab are investigating some experimental vaccines for hepatitis B, influenza, HIV and the Chikungungya virus, cases of which have been occurring in Singapore recently. Currently they are using cellbased assays. The next stage will be tests in animal models.

What are your hopes for the future?

Tong: There are a lot of emerging and reemerging diseases. Historically, we have successfully eradicated just one disease — smallpox in 1979. I think the chances are that most infectious diseases are here to stay because they are very opportunistic; they adapt at any given chance. It is therefore very important to have a strong prevention strategy, and vaccination is a very good intervention strategy for public health. We hope to develop a type of screening, so if any new infectious disease emerges, we would be able to quickly identify potential antigens to focus on, send these to a wet lab, and get out safe and effective vaccines.

There are many exciting developments on our vaccine project, with interest from several local and US venture capitalists. We are currently working on developing a large-scale integrated pipeline for vaccine target discovery from computational modeling to laboratory validation to clinical studies in collaboration with Professor Ren Ee Chee, Principal Investigator at A*STAR's Singapore Immunology Network (SigN).

To read the rest of this article, download the full issue for USD 6.50