Experience

none

Experience

Data Magik has, to date, worked with more than 45 companies from the UK, Europe, Japan and the US and completed in excess of 90 clinical studies.

Our clients range from small biotechnical companies and clinical research organisations to large multinational pharmaceutical and medical device companies.

Our therapeutic expertise is extensive and the list includes: Central Nervous System (CNS), Cardiovascular (Stroke, Hypertension, Arrhythmias, Peripheral Vascular Disease, Pulmonary Arterial Hypertension), Dermatology, Reproductive System (Menopause, Fertility Control), Renal Dialysis, Oncology, Analgesia (Arthritic Pain, Chronic Pain, Migraine) as well as Medical Devices (Stents, Joint Replacement Screws).

We have more built a considerable reputation in CNS particularly within Alzheimer’s Disease (AD), Mild Cognitive Impairment (MCI), Parkinson’s Disease (PD), Schizophrenia and Depression where we have applied specific adaptive design methods.

We also specialise in Phase I trials where we also have considerable experience with other novel statistical designs.

Central Nervous System (CNS)
Analysis of many trials specifically investigating the value of compounds in the treatment of Mild Cognitive Impairment (MCI), Alzheimer’s Disease (AD), Parkinson’s Disease (PD) and Schizophrenia.

Phase I Trials
Pharmacokinetic (PK) evaluation, including bioavailability or bioequivalence after single and repeat dosing.

Biosimilars
The development of all biosimilar products presents many interesting challenges not only for the Clinical experts but also for Statisticians.

Non Linear Mixed Modelling
Non linear modelling is a very specialised arm of statistics. It differs from the standard generalised linear model approach which involves fitting models to data using linear model parameters in that the parameters themselves are nonlinear (eg: power or exponential functions). Where necessary in linear models it is the data that are transformed to allow model fitting.

none
none
none
none
none
none
none
none
none
none
none
none
none
none
none
none
none
none
none
none