How PhDs Can Impress Employers By Understanding The Latest Life Science Industry Trends
I knew that I didn’t want to do a postdoc early on in my PhD studies.
So, during my PhD, I started to figure out what else I could do with my PhD.
What other opportunities were out there for me?
I started looking at the types of positions in industry that a STEM PhD could do and I found out that there were a lot more positions that just bench work available.
But, I wasn’t sure if I was qualified for these positions.
I didn’t have industry experience and most of the work I did as a PhD student was at the bench.
To learn more about the job options that a PhD like me could get into, I set up some informational interviews with people who worked in industry.
And, I found out that while I knew a lot about my research, I knew very little about how things worked in industry.
When I talked to industry professionals, a lot of the concepts and topics they discussed were unfamiliar to me.
They talked about business strategy, new innovations, mergers, and future trends in the industry.
I wanted to be able to have good conversations with the people I was meeting with, so I started to learn more about what’s going on in industry.
I read articles about biopharma, listened to earnings calls, and just paid attention to when new things were happening.
All of a sudden, the conversations I was having started turning into job opportunities.
People were so impressed that a PhD student knew so much about business trends.
It was a great asset to my job search and still enables me to make great connections with the new people that I meet.
Why Tech Innovations Are Important In Life Science And What PhDs Need To Know
In the past few years, the global life science and healthcare industry has experienced significant changes brought about by technical breakthroughs such as CRISPR or implementation of artificial intelligence (AI).
It is also being influenced by external factors, such as geopolitics and new federal regulatory guidelines.
It has been bolstered by promising new technologies and faced challenges, such as a call for more stringent regulation of drug prices.
Despite the challenges, it has managed to strengthen and grow over the past few years.
According to a report by the consulting firm, Deloitte, at the end of 2015 total global health care spending was US$ 7 trillion.
This is expected to grow to US$ 8.7 trillion by 2020.
Some of the key factors driving this noticeable growth include: increased life expectancy resulting in a higher percentage of aging population, growth in the healthcare market in emerging economies, and the introduction of more advanced medical technologies.
This represents opportunities of growth, as well as new challenges for major players in the life science sector.
This growth also indicates more career opportunities for students who are interested in pursuing careers in this sector.
Impress Employers By Understanding These 5 New Technologies Influencing The Life Science Industry
However, before you can capitalize on this growth, it is important to prepare yourself for careers outside of academia.
One of the major drawbacks of PhDs or postdocs who attempt to transition to industry is their lack of awareness of what is going on in the industry.
Science PhDs are highly skilled and knowledgeable in their specific research topic, and this might be sufficient to secure an academic postdoctoral position.
However, if you wish to transition into industry, it is essential to develop awareness of current industry trends.
This awareness, combined with the deep scientific knowledge gained through graduate training, will enable you to portray yourself as the ideal candidate for an industry position in the life science sector.
Overall, the immediate future looks promising, but to continue the positive trend the players in this sector will have to be mindful of the trends and the possible upcoming major changes.
Here are 5 of the top life science industry trends that PhDs need to be aware of…
1. Growing interest in cellular agriculture.
For the past few years, gene-editing tools, such as CRISPR and cell manipulation technologies (such as the engineering of stem cells), have made significant advancement towards developing therapies for various diseases.
However, in addition to developing novel therapeutics, editing and manipulating genes and the engineering of cells are being applied to another new field: cellular agriculture.
Although research associated with cellular agriculture has been going on for the past couple of decades, it has gained significant prominence in the past 2-3 years.
The term cellular agriculture, or “Cell-Ag”, refers to the production and farming of animal products such as meat, fish, leather, or milk by culturing animal cells, rather than harvesting it from the entire animal.
It utilizes various scientific tools associated with biotechnology, such as tissue engineering, fermentation, and cultivating and differentiating stem cells to produce animal products of economic importance in a laboratory rather than on a traditional farm.
Various academic research labs and startups have already successfully conducted small-scale production of several Cell-Ag products.
However, industrial scale production and large-scale commercial availability has not yet been achieved.
Startups in this space expect to launch their lab-grown meat and seafood products before 2025.
One of the startups leading the commercialization of cellular agriculture derived food is Memphis Meats, which was established in 2015 in California.
They successfully produced cell-based meatballs in 2016, and cell-based poultry in 2017.
Other prominent players in this space include Finless Food (California, USA) producing tuna, SuperMeat (Israel) producing poultry, and Mosa Meat (Netherlands) which produced the first lab-made hamburger from cow cells.
Cell-Ag startups are not limited to producing edible animal products.
New Jersey based Modern Meadow is working on producing animal collagen-free, lab-made leather.
Another startup, PEMBIENT (Seattle, USA) is producing bio-fabricated rhinoceros horns to mitigate the issue of illegal horn trade and associated poaching.
As it is well-known, cultivation of livestock is one of the leading contributors of green houses gases responsible for global warming.
According to scientific reports, livestock farming is responsible for 14.5% of global greenhouse emissions.
Moreover, animal farming all around the planet consumes about 16% of freshwater and occupies one third of ice-free land surface.
Growing animal products in the lab will allow us to eliminate these harmful environmental effects.
This novel method of cultivating meat, poultry, and other animal products has the additional benefit of producing the same amount of food while significantly reducing the usage of land, water, and energy.
Cell-Ag derived food is also more likely to be free from pathogens, antibiotics, and hormones associated with meat or poultry obtained through traditional livestock farming, as they will be produced in a controlled laboratory environment.
Considering the positive aspects and financial potential, this new field of cellular agriculture has attracted investments from VC firms, such as Starlight Ventures and Horizons Ventures, as well as visionaries such as Bill Gates and Richard Branson.
Food and agriculture giants like Cargill and Tyson also invested in cellular agriculture startups.
Although cellular agriculture presents significant benefits and economic potential, it faces several challenges.
Besides the technical challenge of large-scale production, the main threats to this new field will be social acceptance among consumers and how new regulatory laws will influence its growth.
2. Application of artificial intelligence towards therapeutics development.
Biomarker development has always been a major aspect of drug development R&D.
Now, Artificial Intelligence (AI) is being applied to this process, and one company involved in it is Berg Health, which has developed AI platforms to identify biomarkers.
In 2017 Sanofi Pasteur announced that they will partner with Berg Health and use 2 AI tools developed by them: “Interrogative Biology” and “bAIcis” to identify biomarkers for vaccine development.
Another organization, Insilico Medicine, is combining the power of deep-learning with blood biochemistry, imaging data, and transcriptomics to develop a biomarker for predicting a subject’ actual “biological” age.
Owing to their potential, AI and machine learning startups have attracted attention of some of the largest biopharma corporations.
In mid-2017, Numerate, a company focusing on implementing AI for drug designing, entered into a multi-year strategic partnership with Takeda.
Their joint research efforts will be aimed at identifying new clinical candidates in the therapeutic areas of oncology, gastroenterology, and neurological disorders.
Application of AI is not limited to drug discovery and the identification of new targets.
It is also being applied to develop autonomous machines capable of treating diseases.
One prime example of this is the collaborative efforts of Medtronic and IBM Watson to develop an insulin pump that will take into account various factors — such as diet, activity, and medical history — and autonomously inject insulin throughout the day, as needed by the patient.
3. Machine learning applied to precision oncology.
The power of machine learning has significant potential in the field of diagnosis and prediction.
This tool can provide data analysis and suggestions that might aid physicians in making more informed decisions regarding diagnosis and determining appropriate treatment.
Memorial Sloan Kettering (MSK) entered into a partnership with IBM Watson to test the feasibility of this method.
The cancer research institute will provide large volumes of data from past cases that will allow “training” of Watson to make evidence-based decisions regarding individualized treatment.
MSK bolsters the Watson’s scientific data using a precision oncology knowledge base known as OncoKB.
These efforts to implement machine learning to determine the ideal treatment options for cancer patients was further enhanced with the partnership between IBM Watson Health and Quest Diagnostics.
This service offers genomic sequencing and analysis of a tumor with the aim of identifying mutations that can be associated with targeted therapies.
The power of IBM Watson is then implemented to compare the detected mutations against relevant medical literature and clinical studies, along with instructions from leading oncologists.
According to current estimates, each month Watson for Genomics is “fed” information from 100 clinical trials and 10,000 peer-reviewed articles.
AI and machine learning startups have been major targets for strategic collaborations for major biopharma organizations.
We can expect to see more partnering and M&A activity in this space.
4. Blockchain for data management in life science.
The security, ease of managing large volumes of data, ability to track any changes made to the database, and secure sharing of data offered by blockchain makes it an attractive tool for healthcare clinical data management.
Blockchain can enable patients to track important health related information, such as a schedule of medical visits, immunization, bills, and personal healthcare records.
One startup, Patientory, is already developing a blockchain-based platform for patients, as well as medical organizations.
Over the years, drug counterfeiting has become a major problem for pharma.
Counterfeit medication leads to about 800,000 deaths each year.
The French startup, Blockpharma, is applying blockchain to solve this issue.
Their technology will enable better tracking of drugs through the supply chain, make it more efficient to recognize counterfeits and alert others.
Considering its ability to securely manage large volumes of data, one healthcare associated field ideal for the application of blockchain is clinical trials.
Blockchain will reduce risk of fraud, loss of data, and improve reproducibility.
5. Amazon enters the healthcare field.
Another aspect of the life science industry that has the potential to result in significant changes is the implementation of technologies for enhancing engagement and productivity of patients or clinical trial subjects.
Tools such as wearables and connected devices, online platforms, and telemedicine will have increasing roles to play in improving data collection and patient involvement.
In 2018, we also saw the first example of encroachment by a major player from a different sector into the healthcare field.
The first instance of this was the acquisition of online drug distributor PillPack by Amazon.
Another example of this is the joint healthcare initiative by Amazon, Berkshire Hathway, and JPMorgan, whose main aim would be to reduce dependence on middlemen and thus reduce the cost of healthcare.
The full implications of these initiatives are not fully understood and this is certainly a field to watch in coming years.
These new technologies not only have disruptive potential, but they also create employment opportunity for skilled professionals with the right technical knowledge. The growth of blockchain, AI, and machine learning in healthcare will require the hiring of a talented workforce and if you are a PhD student interested in these fields, this is the right time to start preparing yourself for it. Some universities are establishing collaborations with major players in these fields to ensure adequate training of their students and to exchange innovative ideas. As a PhD transitioning into industry, it is essential that you understand what is currently happening in your industry. Some of the most recent developments include: a growing interest in cellular agriculture, the application of artificial intelligence toward therapeutics development, machine learning applied to precision oncology, blockchain for data management in life science, and Amazon entering the healthcare field. By staying on top of the latest developments, you can demonstrate that you are a top industry job candidate.
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