Pharma Product Formulation Analytics

A measured quantity of the active pharmaceutical ingredient and excipients makes the right product formulation. The composition, properties, and processing conditions of these ingredients can be prescribed by the deep learning models to formulate a quality compliant product. This is one step ahead of the Quality by Design methodology to achieve the quality goals.

Experimental Data

The experimental data are cleaned, sorted, and unified from different teams in the data warehouses for efficient decision making.

Predictive models

The base models are further hyper-tuned to accurately predict the end-product properties.

Explore Data Signatures

The data signatures unravel the relationship between different input and output variables. The state-of-the-art algorithms could decipher the causal relationship for building predictive models.

Inverse Prescriptive Models

Inverse models are built to prescribe the input properties of the raw materials composition, process variables to effectively formulate the next pharmaceutical product with quality conformance.

How we achieve?

We achieve this with an ecosystem of Machine Learning tools in tandem with our proprietary algorithms. All the IT implementations happens in your native environment. So, adoption of technology is a breeze for your team

How we achieve?

Our engagement?

We engage with our customers as anunconventional accelerator for innovation and digital transformation. DataTheta implements cognitive computing environment to achieve your business goal

Our engagement?

We engage with our customers as anunconventional accelerator for innovation and digital transformation. DataTheta implements cognitive computing environment to achieve your business goal

Hiring machine learning engineers who help you move your project forward can prove difficult given the high market demand for machine learning expertise.Our machine learning engineers fill this talent-gap by jumping in when you need them and partnering up with your team. We accelerate your machine learning project utilizing the right set of skills, so that you do not have to compromise on the speed of the project

Our team of data scientists and machine learning engineers helps you capitalize on your existing resources by bringing your team up-to-speed on the latest in machine learning advancements, all tailored to your knowhow and specific needs.In hands-on sessions, we review practices and techniques in the fields of machine learning, deep learning, computer vision, and NLP, and show you how you can take advantage of them

prototypes is an essential part of scaling robust machine learning systems as they reveal issues and opportunities prior to implementation. DataThetas' research engineers test the functionality of innovative ideas by evaluating your data and building rapid prototypes, so you can eventually move forward with your innovation

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