Successful clinical trials
IDDI innovative biostastics and eclinical solutions are key in the successful conduct of your clinical trials.
Efficient clinical studies start-up and conducts - randomization, data management in a timely manner - user-friendly and cost-effective EDC system - innovative biostatistics methodology
META-ANALYSES OF CLINICAL TRIALS TO SUPPORT NEW DRUG APPROVAL
IDDI has been involved in numerous meta-analyses to directly or indirectly support new drug applications... Read more
ANTI-CANCER DRUG APPROVED BASED ON A SURROGATE ENDPOINTS
We managed to prove, using data from a randomized trial comparing Ceplene + IL-2 to no maintenance treatment... Read more
USING MINIMIZATION FOR A COMPLEX TRIAL DESIGN
A multi-center phase II trial was conducted in just over 100 patients to compare metabolic changes in the prostate after administration of two treatments for locally advanced prostate cancer... Read more.
ANALYSING A BIOMARKER AS A PROOF OF CONCEPT
Two doses of a therapeutic vaccine were tested simultaneously in a randomized phase II trial... Read more
JUMPING AHEAD TO PHASE III
A new ophthalmic drug was going to enter a phase II dose-ranging trial in order to determine the dose to use in phase III trials... Read more
VALIDATING ADVERSE EVENTS ON A LARGE SCALE
Two pivotal trials were conducted (one in the US, one in Europe) to seek approval of a new treatment for a chronic condition in elderly patients... Read more
VALIDATION OF A GENETIC SIGNATURE FOR WOMEN WITH NODE-NEGATIVE BREAST CANCER
A 70-gene signature was shown in a single institution to have prognostic value in patients with node-negative breast cancer... Read more
APPLYING LIKELIHOOD METHOD FOR DATA SAFETY MONITORING
Formal safety monitoring, often performed by independent committees of physicians, biostatisticians and ethicists, has become common in modern clinical trials... Read more
META-ANALYSIS TO ASSESS EFFICACY IN COLORECTAL CANCER
Tumor responses and survival were analyzed combining the data from the different trials using patient individual data... Read more
DISCOVERING NEW PROGNOSTIC BIOMARKERS FOR BREAST CANCER
A range of biological markers were analyzed by polymerase chain reaction and immunohistochemistry in tissue microarrays from patients treated in several past and ongoing clinical trials for breast cancer... Read more
A FLEXIBLE PHASE I TRIAL WITH RANDOMIZATION TO PLACEBO
The maximum tolerated dose of a new drug, supposed to alleviate some adverse effects of anti‑cancer chemotherapy, was to be established in a phase I trial. ...Read more
A BAYESIAN DESIGN FOR A SEAMLESS TRANSITION BETWEEN PHASE II AND III
Data collected by a sponsor suggested a possibility of a differential treatment in subpopulations defined by levels of a biomarker...Read more
SWITCHING FROM PAPER TO EDC
Switching from paper CRFs to EDC not only significantly reduced the time taken issue and respond to queries, it also allowed us to lock our database 2 weeks after the last patient visit... Read more
STATISTICAL EXPERTISE FOR DEVELOPING NEW BIOMARKERS AND DIAGNOSTIC TESTS
IDDI has a long-term collaboration with a Sponsor to provide statistical expertise for developing new biomarkers and diagnostic tests based on Sponsor's proprietary microarray technology ... Read more
A DOUBLE MASKED MINIMIZATION IN OPHTHALMOLOGY STUDY
A phase II study was conducted with a dose-escalation minimization to evaluate the safety, tolerability and efficacy of a treatment in reduction of intraocular pressure in subjects with ocular hypertension or primary open-angle Glaucoma. The study was designed with a double randomization: first the kits were randomized to eye (OD or OS) and then the randomization system (ID-net) performed a stratified minimization on treatment (active or placebo). The dose escalation was managed by using different cohorts automatically closed by the system once the number of expected patients was reached. Our randomization system is flexible and can adapt to studies with a very complex design. It is supported by a 24/7 Help Desk which allows an optimal interaction with Sponsors and Sites during the study.
CLINICAL VALIDITY OF CIRCULATING TUMOUR CELLS IN PATIENTS WITH METASTATIC BREAST CANCER: A POOLED ANALYSYS OF INDIVIDUAL PATIENT DATA.
The purpose of this study was to assess the clinical validity of circulating tumour cell (CTC) quantification for prognostication of patients with metastatic breast cancer by undertaking a pooled analysis of individual patient data. IDDI performed this statistical analysis. These data confirmed the independent prognostic effect of CTC count on progression-free survival and overall survival. This is the first study to show that CTC count also improves the prognostication of metastatic breast cancer when added to full clinicopathological predictive models, whereas serum tumour markers do not.
INDEPENDENT ANALYSES TO INFORM GO/NO-GO DECISIONS
Our client in this case was an investment organization specialized in biotechnology companies, and they required an urgent analysis of clinical data that would be presented on the following week to key decision-makers in the acquisition of a new biotechnology product. The manufacturer of the product had conducted a phase III trial and published the results, but the contract research organization that performed the original statistical analysis was no longer able to provide support to our client. Moreover, there was a need to verify the original results, given the fact that they were negative in the overall trial population, but provided signals of activity in subgroups. By repeating the analyses in only six days and questioning some of the original results presented by the manufacturer in their publication, IDDI was able to better inform their decision-making process.
A SINGLE FRONT-END FOR EDC AND RANDOMIZATION
In a double-blind randomized placebo-controlled Phase II study, IDDI set up a complete integration between its EDC (Marvin) and its Randomization system (ID-net). This was a single front-end for the site.
Full integration means that the randomization is performed by the site using the EDC system, which calls in the background ID-net randomization web services to perform randomization and treatment allocation. The investigator could therefore randomize patients directly from the EDC system without using the randomization system (ID-net).
In this study, a huge number of subjects had to be screened to ensure a total of 200 fully eligible subjects for treatment. IDDI decided to set up two instances in the EDC system, one for the automatic upload of the data coming from the pre-screened subjects and the other instance for the data collection of the eligible and randomized subjects. This particular set up meant a huge save of time in the study conduct.