Anika wants to improve antibody production for the pharma industry
Anika Kofod Petersen will defend her thesis on Monday thereby concluding a year of dedicating her efforts to improving antibody production for the pharmaceutical industry.
For Life Science Engineering and Informatics student Anika Kofod Petersen, it was always essential that her thesis project could have an impact in real life, so when her Danish supervisor Paolo Marcatili offered to reach out to his network at Novo Nordisk for the purpose of carrying out a joint thesis project she grabbed the opportunity with both hands.
‘At Novo Nordisk, they wanted to be able to figure out if an antibody in a drug would work as expected before having to spend vast amounts of time and money developing and testing it,’ she explains.
That challenge was exciting for Anika and so Novo Nordisk co-supervised her project.
Antibody aggregation
The effects of antibodies in drugs used for i.e., cancer treatment and vaccines has gained positive attention in recent years. However, some antibodies tend to aggregate, and researchers do not know exactly how or why. Aggregation increases the risk of having negative reactions to a drug, and the pharmaceutical industry spends enormous amounts of time and money developing and testing drugs, which is why finding new tools for predicting aggregation would be valuable.
The aim of Anika Kofod Petersen’s thesis is to develop a new machine learning tool and compare its performance to existing methods.
‘I have chosen to specialise within machine learning, which is a subbranch of artificial intelligence. Basically, it is all about teaching a machine to learn something, in this case patterns in antibody behaviour,’ Anika Kofod Petersen says.
From growing cells in the lab to writing algorithms behind the screen
On her bachelor’s programme, Anika studied biology and spent a lot of time in the lab, but slowly she has changed her focus towards engineering skills such as programming.
‘Lab work is slow and waiting for results for days due to cells being lazy is not for me. In contrast, there is nothing more satisfying than finding and correcting the flaw in your code and seeing everything work exactly as intended within 30 seconds of pressing Enter,’ says Anika Kofod Petersen, who has spent her thesis analysing huge public data sets and writing algorithms using the programming application Python.
At the time of completing her thesis, it seems that Anika Kofod Petersen has been able to come up with algorithms that outperform those that are currently used in the industry. However, she explains, it raises the question of whether her data was good enough. Therefore, she has been employed by Novo Nordisk to continue working part-time with their data after graduation.
’You must acquire all the advantages you can get’
Anika Kofod Petersen has long been drawn to the pharmaceutical industry, but she is also aware that it is tough.
‘The job market in my field is very competitive, so if you want a head start, you must acquire all the advantages you can get. The double degree I get at SDC is definitely an advantage, but it is also my understanding that you need a PhD to land a good job in this industry,’ she says.
In the immediate future, Anika Kofod Petersen will continue working on her thesis subject using data gathered by Novo Nordisk while she looks for a PhD position.
Follow Anika on Instagram THIS WEEK where she is doing a take-over of the @sinodanishcenter Instagram account.