Reimagining Drug Discovery And Testing To Increase Genetic Data For Black People

Reimagining Drug Discovery And Testing To Increase Genetic Data For Black People

genetic data
Non-covalent hydrogen bonds betwixt base pairs of the DNA-double-helix visualized through an electron microscope. Image: Karl-Ludwig Poggemann / Flickr

Artificial intelligence is increasing the speed of new drug discovery, but what does this matter if Black patients don’t respond well to the drugs?

Traditional drug discovery at big pharmaceutical companies is a long, arduous process of scientists conducting laboratory experiments and visually reviewing results to identify how different cells respond to a drug.

After years of research, companies test these drugs to see which ones work. At the end of the day, typically one in 10 potential drug treatments turn out to be viable for the market.

This is expensive for pharmaceutical companies that invest billions of dollars in research and development to identify the next game-changing drug that could deliver a strong return for their shareholders. Put yourself in the shoes of an investor who holds a lot of stock in a large pharmaceutical company and you can imagine how a one-in-10 success rate could get old.

Artificial intelligence and drug discovery

Enter artificial intelligence. Through machine learning, research scientists are able to have computers look at thousands of cells and how they react to drug compounds to identify a new drug.

One company, GlaxoSmithKline, is using deep learning to mimic how our brains identify patterns and examine millions of combinations of genes to understand how they operate functionally in each others’ presence. This work enables quicker discovery of a working drug because researchers are able to determine the particular genetic makeup that would respond to it.

This is great stuff. There are thousands of diseases around the world and speeding up the rate at which we can address those diseases is a good thing.

2 Problems exclude Black people from drug discovery

Companies like GlaxoSmithKline need tons of genetic data to effectively determine the genetic makeup that would respond well to a particular drug.

There are significantly lower levels of genetic data available for Black people than Europeans. A group of researchers at the European Bioinformatics Institute analyzed ancestry data in genomics studies and found that nearly 80 percent of the data used in these studies were of European descent.

How much progress is really being made if your drug potentially doesn’t work on a large swath of the global population and you don’t have the data to give a firm answer one way or the other?

Further, the process companies go through in testing their drugs hasn’t gone through the same level of innovation that drug discovery has. In the U.S., African Americans are historically underrepresented in clinical trials.

This is a reality for a range of reasons including distrust of experimental research stemming from memories of the Tuskegee syphilis experiment and the cost-prohibitive nature of some clinical trials that can require lots of travel to wherever researchers are conducting the trial.

Reimagining drug discovery, testing and genetic data

What would it look like for researchers to partner with people from underrepresented populations in their genetic datasets and find ways to expand their datasets in ways that provide real value for people giving up their data?

Listen to GHOGH with Jamarlin Martin | Episode 33: Dr. Gina Paige

Jamarlin talks to Dr. Gina Paige about African Ancestry, the company that used DNA to pioneer a new way of tracing African lineages and helped 500,000+ people reconnect with their roots.

23andMe is one of the more prominent companies trying to figure out ways to create win-win situations for populations across Africa in giving up their data. African researchers have voiced their displeasure with the U.S. company and others like it taking data from the continent. Yet, there’s no real alternative.

African Ancestry — a company that used DNA to pioneer a new way of tracing African lineages and helped 500,000+ people reconnect with their roots — doesn’t sell the data it collects to companies.

Further, I’ve been looking for Black-owned pharmaceutical companies in the U.S. and I have yet to find one. Perhaps there’s an opportunity there to have people from the Black community start companies developing drugs that address diseases impacting Black people? The rise of machine and deep learning in the space reduces the barrier to entry that new players could take advantage of.

In regards to drug testing, there have to be opportunities to reimagine how clinical trials take place.  The rise of telemedicine and sophisticated health monitoring capabilities from our mobile phones must create opportunities to change how researchers have traditionally conducted clinical trials. What would it look like for clinical trials to meet patients where they live or work? What if there are ways to incorporate mobile technology into the process of monitoring patients?

The speed with which drug discovery methods advance is only going to increase as artificial intelligence technology matures. It would be a shame to see these advances not have an impact on underrepresented groups around the world, whether that’s through the discovery process or the testing. This will be a space to watch how researchers and pharmaceutical companies innovate to increase the impact of their discoveries.

Kwame Som-Pimpong leverages relentless research, a knack for connecting dots, human-centered design approach, and effective communications strategy to help organizations realize their strategic objectives. Over a 10-year career, Kwame has supercharged grassroots political organizing efforts, assessed the effectiveness of U.S. federal agencies, managed an international program, founded a digital media startup, and advised government agencies on delighting their end-users. He earned a BA in Political Science from Davidson College and Master of Public Administration from the University of Georgia.