We provide a design platform for acquiring assets for discovering new drugs. We use data processing and control software to rapidly conduct millions of chemical tests to arrive at the clinical trial process. We also conduct pre-clinical research methods to determine the properties of the drug. These research and trials will be conducted by a scientist with the government allowed drugs.
When working on a research and development process, there is going to be a lot of data to acquire and analyse for certain results. At Statswork, we streamline those data and normalize it and display it in a sophisticated dashboard that can be read and understood by a research scientist. These dashboards are fed into your system through APIs, which we have created.
We optimize patient Recruitment by developing algorithms and predictive models to identify suitable participants for clinical trials. Our experts also carry out real-world Evidence (RWE) Analysis by analysing real-world patient data to inform clinical trial design and decision-making.
We at Statswork recognize the data and analysis required for the life science industry and produce better solutions using machine learning and artificial intelligence to generate insights on the products, which helps to grow your business. We collect millions of data points from your unstructured data and produce models that can forecast the sales profits to increase your business return on interest.
We develop Virtual Screening by using computational methods to screen chemical compounds and predict potential drug candidates.
Pharmacophore Modeling: Identifying key chemical features for drug-target interactions.
ADME (Absorption, Distribution, Metabolism, Excretion) Modeling: Predicting a drug’s pharmacokinetic properties.
Toxicity Prediction: Assessing the safety of drug candidates using predictive models.
We have capability to conduct varied epidemiological Studies including analysing disease patterns, transmission dynamics, and risk factors using epidemiological data. Further, we conduct population Genetics by studying genetic variations in populations to understand disease susceptibility.
We have capability to carry out electronic Health Records (EHR) Analysis by extracting insights from patient records, including disease diagnosis, treatment outcomes, and patient management. We also conduct predictive analytics by developing models for disease prediction, patient risk stratification, and healthcare resource optimization.
Our Image Analysis Services at Statswork encompass diverse applications. We specialize in Medical Imaging, where we develop advanced image analysis algorithms tailored for various medical imaging modalities such as MRI, CT scans, and microscopy. Additionally, our proficiency extends to Pathology Image Analysis, where we automate the analysis of pathology slides to facilitate disease diagnosis and grading. Through these cutting-edge image analysis techniques, Statswork contributes significantly to the fields of healthcare and life sciences.
We develop Virtual Screening by using computational methods to screen chemical compounds and predict potential drug candidates.
Our NLP solutions extract valuable insights from unstructured medical texts, including clinical notes, research articles, and patient records, facilitating information retrieval and knowledge extraction.
We create machine learning models for disease diagnosis, image analysis, and medical imaging interpretation. These models assist healthcare providers in making accurate and timely diagnoses.
We at StatsWork have qualified researchers and scientists who can find out which drug is being considered for trial and which companies are interested in conducting those trials. We also use try to find out which technologies are used to manufacture those drugs. We also provide analysis on which processes need to be automated to produce the drug faster in time than your other competitors.
When a new medicine rolls out to the public, patients who ingest the drug might have some issues with it. We collect complaints data of the released new drug from the patients and analyse the sentiment of the comments. We have built a machine learning NLP model which classifies the comments as good, bad or neutral, which in turn can explain the issues with the drug, and the company can then update the drug, which can be used by the public without any problem.
The manufacturing process in the pharmaceutical companies is difficult to process, and if it is not overseen properly, then it might lead to money loss and a decrease ineffectiveness of the medicine. We have built artificial intelligence models which can assist the manufacturing process and can increase its speed of it by at least 20%. This additional time can be used for quality detection from the manufacturing process.
To attend the diverse needs of the global clients, dedicated pool of resources, managed by Customer and local offshore project and account manager, research and support team.
To attend the diverse needs of the global clients, dedicated pool of resources, managed by Customer and local offshore project and account manager, research and support team.
To attend the diverse needs of the global clients, dedicated pool of resources, managed by Customer and local offshore project and account manager, research and support team.
To attend the diverse needs of the global clients, dedicated pool of resources, managed by Customer and local offshore project and account manager, research and support team.
