Thought Leadership

Cognitive Chronicles

Hybrid Conjoint: Precise Prediction without Limitations

Cognitive analyzed 300+ pipeline launches and identified the factors most correlated with commercial success. This analysis led to a demand framework that maximizes peak go-to-market performance that stays viable long term.

Our demand framework, known as the Hybrid Conjoint, combines the best components of the traditional method to support significant market unknowns, potential clinical endpoints, multiple Target Product Profiles, various current and future competitors, and iterations of numerous patient types. It can accommodate an extreme number of attributes and an even greater number of levels that produce trillions of potential combinations.

You don’t know what you don’t know, so let Cognitive’s Hybrid Conjoint simulate the limitless potential outcomes that endure over time.

Cognitive Chronicles

Unlocking Data Using Quadratic AI: Everything Everywhere All at Once

Quadratic AI is next generation data analytics that empowers marketing and brand teams to analyze, predict, and act, all in one. It is a non-linear machine learning technique to improve various stages of brand development, insight optimization, and outcome prediction. Advanced AI models including generative and predictive AI are being integrated into pharmaceutical brand launches to enhance efficiency, precision, and market impact.

• Feature Engineering (pattern discovery), Quadratic Regression (least squares equations), Machine Leaning Models (support vector machines)

Through Quadratic AI, Cognitive can help with:

• Disconnected data sources
• Time consuming manual reporting
• Limited predictive capabilities
• Lack of real-time insight

Cognitive Chronicles

Do What’s Right, Not What’s Easy: Cognitive Remains Methodologically Agnostic

We won’t stamp out an approach simply because it’s easy for us. We fully customize a holistic strategy that meets our clients’ unique needs each and every time.

Our strategy hinges on four distinct areas of opportunity in market research. The first involves supporting current practices by making them faster, cheaper, or easier to scale. The second includes replacing current practices by leveraging synthetic data (data created by AI to model preferences or behavior to amplify primary and secondary research). The third fills existing gaps in market understanding by obtaining insights and evidence available outside the parameters of conventional data. And the fourth, which is still emerging, involves creating new types of data and insight discovery.

Cognitive Chronicles

Augmenting Healthcare with AI: More Intelligence, Less Artificial

Cognitive believes that AI amplifies and augments, rather than replaces, human intelligence. When implementing AI systems in healthcare, it is key to preserve the important elements of human interpretation in research while harnessing AI to make interactions more efficient and effective.

Integral to utilizing AI, Machine Learning unlocks the value of data. It uniquely handles the velocity, volume, and variety of data generated by new delivery processes and the next generation of atomized and scaled out applications.  It also identifies true customer segments, improves forecast precision, and helps to expand into new opportunities, ultimately elevating customer engagement, deeper insights, and unknowable consequences and discovery.

Cognitive Chronicles

Precision Medicine: Right Treatment, Right Patient, Right Time

Advances in technology have the potential to transform many aspects of healthcare, enabling a future that is more personalized, precise, predictive, and portable.

Modern consumers want fast, easy access to information. They want engaging and personal interactions. The healthcare industry is no exception. Yet continually rising costs, disparate systems, and a lack of patient engagement create delays and complications in providing appropriate care. The prescription is simple: Precision Medicine. 

Cognitive Chronicles

The 340B Balancing Act: Preserving Program Integrity through Transparency and Accountability

340B was originally established in 1992 to increase patient access and treatment affordability. In the years since, the program has grown to encompass a greater number of hospital systems (“covered entities”) and a higher volume of eligible patients. Drug manufacturers provide 340B discounts on drug purchases by covered entities serving medically underserved populations, and those drugs are commonly dispensed through retail “contract pharmacies.” This expansion contributes to increased affordability, but duplicate discounts could also occur due to overlapping prescription eligibility. Currently, there is no universally accepted method for identifying such claims. Both state and federal policymakers, including the Health Resources and Services Administration (HRSA) and the Centers for Medicare & Medicaid Services (CMS), have been addressing duplicate discounts, but a complete solution remains elusive.

Cognitive discovered that preserving the integrity of the 340B program involves a Trust Trifecta. (1) Connection: Bridging communication between covered entities and manufacturers can help mitigate program impacts. (2) Authenticity: Maintaining confidentiality of PII affords data integrity and promotes confidence. (3) Competence: Establishing financial reliability, consistency, and accountability allows for a symbiotic relationship.