
I'm a computational biologist with a strong foundation in molecular biology and Python-based data analysis, focusing on protein druggability assessment. I've successfully collaborated with tech startups such as Deep Knowledge Group and AION Labs, as well as research laboratories in Sick Kids and Diagen. Equipped with a BSc in Molecular Biology and an MRes in Drug Design from UCL, I presently serve as the Head of Life Sciences Research at Deep Pharma Intelligence. My dedication to innovation and my expertise in the convergence of data science and the pharmaceutical industry fuel my ambition to excel in leadership roles, particularly in the fields of bioinformatics and drug discovery.
After six months at Aging Analytics Agency (AAA), a subsidiary of Deep Knowledge Group (DKG), I earned a promotion to the position of Head of Life Sciences Research at Deep Pharma Intelligence (DPI), another DKG subsidiary. My strong analytical abilities and leadership qualities garnered recognition. Beyond analytical tasks, my proficiency in data science facilitated seamless collaboration between the life sciences and data science departments, driving enhanced automation of our products. I also actively contributed to business development initiatives, including negotiations with companies such as Clarivate and Takeda.
As a Scientific Analyst in Aging Analytics Agency (AAA), a subsidiary of Deep Knowledge Group (DKG), I was responsible for conducting research, analysing data, and presenting insights related to target markets with a specific focus on Aging, Longevity, Biomarkers discovery, and Aging-related diseases. With a strong background in computer science and a degree in life sciences, I was able to leverage my expertise in data mining, statistics, and graph algorithms to deliver on diverse project tasks.
During my time in this role, I developed excellent written, verbal, and visual communication skills and was able to apply critical thinking to a wide variety of problems. My ability to work collaboratively in a cross-functional team, along with my proficiency in MS Office and Google Workspace, has allowed me to effectively contribute to the success of the projects I worked on.
I am proud to have contributed to the world's leading high-tech business with a company that values scientific innovation and expertise.
AION Labs, in collaboration with BioMed X, established a startup incubator for the project 'De Novo Computational Design of Therapeutic Antibodies.' Notably, I, being the only participant without a Ph.D., was selected among the top 15, standing out as the youngest member. The camp focused on proposing a mechanism for a machine learning-based platform for antibody design. In just 5 days, working in diverse teams, we honed teamwork, communication, and presentation skills under significant pressure. Proposals were evaluated by Pharma industry leaders like Pfizer, AstraZeneca, Merck, and Teva. Despite my non-traditional background, my skills were highly evaluated on par with postdoc participants, showcasing the value of interdisciplinary expertise. This experience broadened my understanding of current antibody design approaches, enhancing my creative thinking for unsolved problems.
First Bridge is an R&D company that develops technology for various fields. My role is to consult the company regarding potential collaborations with biotech startups. My multidisciplinary background in both bilgy and computational technologies allowed me to evaluate how a technological know-how developed by First Bridge can be implemented to improve biotech products of collaborators. Besides the technological knowledge, this position also requires deep understanding of business aspects of the problems, as well as creative thinking to come up with economically beneficial solutions.
Diagen was the first laboratory in Ukraine to create PCR kits for the coronavirus testing, now used by the whole country. I started as a volunteer to help with the high demand of the covid tests where my DNA extraction and PCR skills were useful. Eventually, I started working in gerontology research department investigations, such as linking the change in number of mitochondria in the cells with ageing and the role of specific alleles in ageing. I also participated in a research for genetics passports that Diagen was making, where the whole genome is sequenced and analysed. I was performing literature search for allele interpretation and pyrosequencing. Because of the pandemic, many reagents were impossible to be ordered from abroad, so we had to adjust the PCR for the new reagents that were available. This has significantly developed my skills in problem solving and experimental adjustment to available conditions.
This was my first experience of contributing to a real research paper, investigating the effect of stem cells extracellular vesicles intrauterine injections effect on congenital diaphragmatic hernia (CDH) development in nitrofeninduced rat models. I was taught to culture stem cells, extract miRNA, perform miRNA qPCR, dissect rat embryos, prepare lung and kidney slides, do hematoxylin and eosin staining, immunofluorescence co staining, imaging with confocal microscopy and histological analysis of lung and kidney branching. In addition to lab skills, I learned how to plan the experiment, choose appropriate reagents and order them.
I organised social events ( up to 150 people), cooperate with other societies and manage our social networks. In 2022 year I was highly involved in charity events to support Ukraine.
As a course representative of my year group BSc Biotechnology and MRes Drug Design, I contacted with course organisers about any changes should be done to the course, collected and present the feedback from my course-mates about the educational process.
I was cited in The Guardian Article: 'Global survey finds diabetes goes undiagnosed in 40% of cases' as the lead researcher of the 'Global Diabetes Industry Overview 2023' report, published on behalf of Aging Analytics Agency. The article discusses the significant findings from the report, highlighting my role as the lead researcher in this impactful publication.
Regular Speaker at Tokyo-1 clients meetings (since August 2023) presenting 'AI in Drug Discovery Industry' reports, contributing to technology collaboration between Mitsui & Co., Ltd. and NVIDIA to boost Japan's pharmaceutical industry.
Debating competitions:
• Reachedthefinalroundof"CardiffDebates2017"inBritishParliamentformat
• Winnerof"DebatingMatters2016"competitioninCardiff
• ReachedthefinalroundoftrialstoentertheWelshnationaldebatingteamin2017,
international debating format
2nd place in the 2016 IntelEco Ukraine research competition for "Retrospective Analysis of Avian Chlamydiosis Spread in Kyiv" project
'Introduction to Data Science' specialisation taught by IBM
Obtaining this 4 months long specialisation I have learnt data science methodologies, had an experience of working with various tools like R studio, Jupiter lab, IBM cloud and others. Gained a skill of analysing real datasets using python and SQL.
'Introduction to Genomic Technologies' online course taught by John Hopkins University
This course is part of an online specialisation in 'Genomic Data Science' that I am currently pursuing. It is enhancing my skills in bioinformatics, data analysis, and statistical techniques for interpreting genetic data. This specialised training will empower me to effectively utilise genomic data for research and analysis.
Computational Analysis and Prediction of Protein Targets Druggability
I conducted a research 'Computational analysis and prediction of protein targets druggability' during my Master of Reseach program at UCL. In this work I performed a deep analysis of all known targets and their drugs, developed a machine learning algorithm to predict how likely a potential target is to be drugged by orally bioavailable molecules. During this project I developed my Python programming skills and data analysis. I worked with big data from biological databases, such as ChEMBL, DrugBank, PDB, UniProt, Pfam and SCOP. AEmploying advanced techniques like random forest and linear regression, I created a predictive model assessing protein draggability at the protein family level. This research unraveled promising protein families and specific drug classes with potential for effective targeting of those families.
Retrospective Analysis of Avian Chlamydiosis Spread in Kyiv
In high school, I conducted a 6-month research project titled "Retrospective Analysis of Avian Chlamydiosis Spread in Kyiv". I collected and tested pigeon samples from various districts of Kyiv, using PCR analysis to detect chlamydiosis. The aim was to raise awareness of avian chlamydiosis's significant spread, its threat to humans, identify the most affected areas, and advocate for bird quarantine measures. This research earned me second place in the 2016 IntelEco Ukraine research competition.