A leading biotechnology company developing therapies for age-related and neurodegenerative diseases needed specialized data expertise to accelerate translational research and therapeutic development. While their internal teams excelled in biology and clinical strategy, they required deeper technical capabilities across data science, biostatistics, bioinformatics, real-world data, and data architecture. To scale their analysis efforts and maintain high standards of data quality, reproducibility, and compliance, the company sought external support to strengthen its data infrastructure and analytics ecosystem.
The client’s research involved large-scale biological, clinical, and real-world datasets, including omics, EMR/EHR, and claims data. To accelerate discovery, they needed to design interoperable data systems, harmonize data sources, and implement statistical models capable of deriving meaningful insights. Identifying talent with both technical proficiency and domain understanding in biotechnology and healthcare data, proved difficult in an already competitive market.
The ALKU Data and AI Team partnered closely with the client’s leadership to identify and onboard specialized consultants across data science, biostatistics, bioinformatics, data architecture, and real-world data integration. A real-world data specialist would be needed to integrate and harmonize diverse RWD sources, including claims, EMR/EHR, and lab data, aligning with OMOP and other industry data models as well as identify data gaps and improve data completeness and usability for downstream analytics. A biostatistician was also identified as needed to design and apply statistical models for longitudinal and multi-omics datasets related to neurodegenerative diseases. They would also perform power analyses and collaborate with neuroscientists and bioinformaticians to interpret biological signals and biomarkers.
A data scientist, two senior data scientists, and a senior data architect were also added by ALKU’s Data and AI Team to keep the project on track. The Data Scientists were brought on to build and optimize data pipelines and analytical workflows in Python, R, and SQL, develop predictive models and machine learning algorithms for high-dimensional datasets, and deliver insights to cross-functional research and clinical teams.
The Senior Data Architect would design and implement scalable, compliant data solutions across cloud environments; develop frameworks to integrate internal and external data sources, ensure adherence to standards such as OMOP, FHIR, and HL7, and supported regulatory alignment and governance.
Each consultant was selected for their ability to operate in a highly regulated environment, combining technical rigor with scientific understanding to ensure that data infrastructure and analytical outputs met both research and compliance needs.
Together, these specialists enabled the client to succeed in a variety of different ways. They established scalable, interoperable data systems supporting scientific and clinical use cases. Biomarker discovery and translational research were accelerated through reproducible data workflows. They generated real-world evidence (RWE) from integrated datasets to inform therapeutic strategy. Compliance and data governance were strengthened through standardized architecture and documentation. These consultants provided the technical foundation for ongoing research and clinical initiatives in age-related and neurodegenerative diseases, helping transform complex data into actionable insights for therapeutic advancement.
The ALKU Data and AI Team was tasked with forming a team of data experts in the biotechnology and pharmaceutical industry. These roles each contained highly specialized skill sets that would make or break the project being established. The team not only successfully introduced six experts to aid the client, but also did so quickly and efficiently, with constant communication between ALKU and the client. Discover how ALKU’s Data and AI Consulting Services can drive measurable value for your organization, leverage the latest in data science and business innovation, or connect with our team to discuss your next AI transformation initiative.