Vivek Sharma, CEO, Saama Technologies
Pharmaceutical companies often have to run tens of thousands of clinical studies with millions of datasets. With so many data points, effective data analysis is now more important than ever to make confident business decisions for better clinical trial outcomes. Missing data and manual workflows can lead to costly mistakes that waste precious resources and time, or at worst put the entire clinical trial at risk. Given the myriad of challenges that coincide with clinical trials, bringing a novel drug or treatment to market becomes a protracted, painstaking, and often costly process. Saama Technologies helps pharma and life science companies navigate this complex landscape and successfully provide patients with life-saving medications.
Saama is the driving force behind the life science industry’s current evolution from e-clinical to ClinTech, the exciting new category of purpose-built, AI-based clinical insights and automation platforms that is changing the face of clinical development. Saama is committed to protecting and promoting human health by empowering the pharma and life science industry to conduct faster and safer clinical development and deliver new therapeutic options to the patients who need them. The company has developed an award-winning, proprietary Life Science Analytics Cloud (LSAC) platform to deliver game-changing solutions that improve clinical trial outcomes. LSAC’s robust applications provide control and automation of comprehensive clinical research data. With the help of these applications, organizations can file New Drug Applications (NDAs) more quickly and effectively and bring therapies to patients faster than ever. Today, more than 50 biotech companies, including top 20 pharmaceutical companies, are using the platform to accelerate clinical research, including the clinical trial that led to the world’s first COVID-19 vaccine.
Transforming Data into Life-Changing Insights
Saama primarily focuses on addressing the critical drug development challenges faced by pharma and biotech companies and obliterating these pain points with the use of science and technology. Its LSAC platform leverages the potential of AI and deep learning to help clinical trial sponsors and contracts research organizations (CROs) integrate, curate, and animate data for effective problem solving across clinical operations, medical review, data management, biostatistics, and pharmacovigilance.
Partnering with Pfizer, Saama leveraged its domain-centric, deep learning/AI system called Smart Data Quality (SDQ) to help them bring the world’s first COVID-19 vaccine to patients before any other company. “SDQ processed tens of millions of data points for Pfizer’s 44,000-person trial. It shaved one month off the vaccine’s clinical development timeline, ensured data quality, and enabled scientists to review patient data only 22 hours after the clinical trial ended – something that usually takes over one month,” elucidates Vivek Sharma, CEO of Saama Technologies. In addition to the initial clinical trial, Saama has continued to partner with Pfizer over the past year to leverage SDQ in subsequent COVID-19 vaccine studies for younger age groups.
Fostering a Culture of Innovation, Creativity, and Leadership
Apart from its customer-centric solution and services, the core attribute which played a critical role in the success story of Saama is its people and inspiring work culture. According to Vivek, creating a dynamic and collaborative culture is vital to the success of any organization. Saama strives to maintain a cooperative company culture where all Saamaites feel safe, respected, valued, and motivated. Saama leadership empowers the global team with the confidence that they can create drug development products and services that will uplift the quality of life for humanity.
Cultivating a Trusted Partnership with Customers
Highly committed to customer success, Saama always places the needs of its customers at the forefront and thus cultivates a strong customer relationship. It holds quarterly product advisory board meetings with customers and industry leaders to help guide its product roadmap, as well as executive roundtables to listen to their challenges and needs. Even during the pandemic, when in-person events and learning opportunities were curtailed, Saama conducted two virtual executive roundtable events; one for top pharma and another for small-to-mid biotechs. The company always stays abreast of current industry trends, guidance and regulations so its customers don’t have to. “Many of our customers don’t have internal data analytics teams and therefore rely on Saama’s expertise and experience. We also have a strong presence within industry associations,” affirms Vivek. Saama is a member of the Clinical Data Interchange Standards Consortium (CDISC) and Avoca Quality.
Set To Work on Unknown, Rare Diseases
Backed with a winning work culture, customer-centric approach, and value proposition, Saama has garnered a broad customer base across the globe. But despite this clearly positive customer response, Saama is not resting on its laurels and is committed to continually improving its services to remain the partner of choice for pharmaceutical companies to accelerate end-to-end clinical development timelines to bring drugs to market faster than ever. “Since the advent of modern medicine over the last two centuries, there has been much progress. However, it has been limited to creating cures and preventions for less than ten percent of known illnesses. Saama is committed to replicating that success to address the other 90 percent of human disease,” adds Vivek.
Forging ahead, the company also plans to work on many unknown, rare diseases through partnerships with biotech customers. From a financial standpoint, it is very expensive to create pharmaceuticals to treat uncommon diseases, and Saama knows that reducing the time and cost of developing such drugs will allow biotech companies to focus on rare diseases as a viable option. Besides this, the lack of participants and data points in studies for rare diseases has historically been a problem. Thus, Saama aims to address the issue with its machine learning solutions that can build predictive models with minimal data. “Speed and quality are two big issues in rare disease drug development, and Saama intends to enable both, helping biopharmaceuticals produce safer and more effective therapies for rare as well as more common diseases,” concludes Vivek.