Kenya could Implement Personalized Medicine in the Next Five Years
By Mary Hearty
Kenya has the potential to implement personalized medicine- a medical model that is used to determine the genetic makeup of a person in order to know the best drug that is specifically suitable for them- in the next five years with strong collaboration among stakeholders in the healthcare sector.
This is according to Prof Walter Jaoko, Professor of medical microbiology and tropical medicine, and director of the Kenya Aids Vaccine Initiative (KAVI) Institute of Clinical Research during an interview with Science Africa at the European Union-East Africa Regional Stakeholder Workshop on Personalized Medicine.
Prof Jaoko said that the essence of the workshop was to stir up scientists, researchers, and healthcare personnel to work together so that they can speed up the process of implementing personalized medicine.
“From the collaboration we have had with different countries like Uganda, Tanzania, Ethiopia, Rwanda, Zimbabwe, and South Africa. The idea is to meet together in form of a taskforce or consortia and plan for each respective country what the next step would be. I believe that in Kenya we will be able to do it sooner than later,” he noted.
Prof Jaoko said the existing regional collaboration would play a major role in the implementation of this medical model to ensure that some expertise that may not be available in some countries, can be outsourced from neighbouring countries, noting that the whole idea is to help each other in the region.
Nevertheless, he noted that the East African countries do not have to wait for each other but can tap from each other’s expertise.
Why the need for Implementing PM?
“We know that the drugs that we use currently have been tested on many people, so we believe, that it can work in many people, but we know that it cannot work in some people. But with personalized medicine, we will be able to evaluate your genetic makeup, then match the drug that is suitable to you as an individual,” Prof. Jaoko said. “We want to be sure that the medicine that we are giving you, will really work.”
Additionally, he said the project has already taken off in North America and Europe and even Japan, so Africa should not be left behind.
In Kenya, Prof Jaoko said the medical model would be very beneficial in the case of cancer, especially breast cancer in women which he explained that two women with the disease may be given the same drugs, but only one feels better afterwards while the other does not respond to the treatment, hence dies.
“So, with personalized medicine, we will be able to look at the genetics of these two women, and then be able to know which drug is specifically suitable to each of their genetic makeups,” Prof Jaoko explained.
Besides, Prof. Jaoko noted that personalized medicine reduces the cost of treatment as the wastage of medicine on people it might not work on is reduced due to the treatment being specific.
He clarified that this has nothing to with addressing the issue of antimicrobial resistance, however, the healthcare professional will be able to determine the drug which works best for the patient.
In addition, Prof. Jaoko noted that this will not need manufacturing of other medicines even though drug development is a continuous process. “We will map the drugs including the new ones to determine which population they work best in,” he said.
What it takes
In order to ensure effective implementation of this promising medical model, Prof Jaoko elaborated that comprehensive understanding of people’s genetic makeup will be key, though, a lot of genetic makeup has not been done in the African region, Kenya included.
In this regard, Prof Jaoko advised that a lot of genetics studies need to be done so that when patients go to the hospital, their genetic makeup would be known immediately. “We need to know what your genetic makeup is and which drug can be used to treat your particular condition,” he said.
Dr Evelyn Gitau, Director of Research Capacity Strengthening at the African Population and Health Research Centre (APHRC), and one of the stakeholders at the workshop reaffirmed Kenya’s potential in implementation of personalized medicine, noting that the country already has some personnel in terms of capacity, though not enough.
“The biggest issue and the easiest part with so much impact to ensure effective implementation of this personalized medicine is building the critical mass. The more people we have working in a space, the cheaper it becomes and the faster the results will be achieved as more data will be produced. This includes policy makers who understand personalized medicine, patient advocates among others.”
Dr Gitau also called for the need to set up infrastructure for these personnel to actually utilize their skills. “The issue of infrastructure has led to brain drain as a lot of the country’s experts in this field are not working in the country. But with this opportunity, this could stop as they will be able to work within the country.”
In addition, she said the issues around human genomic data may be a barrier in the implementation process because the Data and Protection Act has not yet been unpacked to allow scientists see how best they can use data from human genome sequencing. “We need to unpack some regulatory frameworks to allow us to fully explore and utilize personalized medicine,” Dr. Gitau said.
Additionally, she said: “We just need to perhaps accelerate some of the things like local funding to drive some of the resources using big data.
“Money for research and development which is supposed to be at 2% of the GDP is still at 0.9% and it is distributed to other research areas like livestock, agriculture, and climate. That is not enough to scale up health research especially in these kind of projects.”
Since the medical model has many levels- individual level, population level, Dr. Gitau added that the already existing data at the Ministry of Health could allow scientists to look at personalized medicine at population level but the capacity for artificial intelligence and data science will be needed.
“We need more data scientists, train them and put them in the personalized medicine system so that they can develop frameworks and platforms in order to store and utilize the data appropriately.”