This section allows to review and compare topline clinical trial results (ORR, PFS / DFS and OS and the corresponding hazard ratios / risk reductions). Results can be analyzed for a given tumor and a selected line of treatment and can also be combined with open text search like mechanism of action (e.g “CDK4/6 inhibitor”). All available filters (e.g. Immuno-Oncology etc.) can be used and combined. Cross-trial comparisons should be considered as “hypothesis generating” and different inclusion and exclusion criterias might strongly influence the result.
This section allows to review the launch timelines by tumor, by company or by whatever combination of filters that has been selected. We use the following approach to estimate regulatory approval timelines: the industry standard for the preparation of a dossier for regulatory filing is 4 months (the time needed from data readout until regulatory filing). Approval timelines in Europe are estimated to be 12 months for new molecules and 9 months for new indications (type II variation). For the US we use 6 months as an estimate for all approval timelines based on the FDA track record in the last years. Data readout timelines are based on data from clinicaltrials.gov or, where available, on information provided by the companies. Timelines are updated on a constant basis whenever new information becomes available. We do permit that the resulting graphics are exported (e.g. screenshot used for a power point presentation) but only for internal presentations and only when the information “Source: OncologyPipeline” is clearly visible on the slide or document.
This section allows to analyze the success rates of the different trials per tumor and per company. Across all projects in the OncologyPipeline database the success rate stands at around 70%. This rate is unrealistically high given that the programs span all development stages. The most likely reasons for this high success rate are: 1. Underreporting of negative trial results (negative results tend to be published less), 2. Programs that seem to have positive results (“showed encouraging efficacy and acceptable safety in this phase 1 trial”) but then later are stopped for a variety of reasons. Our evaluation of a positive or negative result is based on reported results and conclusions at scientific meetings. The checkbox “Trials with overdue results (> 12 mts) are counted as negative trials” allows to count those trials as negative trials and thereby reducing the overall success rate. Another checkbox above the table allows to select “Phase III results only” - this results in an overall success rate of ca. 55% which is very much in line with published literature. Note: the phase III checkbox in the development stage section of the filters does not take into account phase III trials that have been filed or approved (these trials are included in “CHMP/FDA/NMPA”, “CHMP+” or “Approved”). In order to include also the phase III trials that have been filed or approved we created the special checkbox “Phase III results only” specifically for this section
In this section we provide a selection of trials that we consider are the most relevant, interesting and impressive. For example, trials that have generated practice changing results are included in this section – some of the criteria we use to classify a project as “best of” are low hazard ratios for PFS and OS (meaning a high reduction in the risk of progression and death), Breakthrough Therapy Designation by the FDA and / or publication in the NEJM. We also include trials in the best of section where the results are not yet known (e.g. phase III) but where the drug or combination of drugs have generated highly promising early stage results. The best of selection is a fast and easy way to get to know the most promising drugs and trials in Oncology and Hematology today.
The key timelines sections allows to analyze study and filing timelines as well as regulatory approval timelines. We suggest to activate the checkbox “Only display projects with actual or foreseen approval date” in order to focus on late-stage projects with actual or planned timelines. This section allows for example to benchmark how long certain trials took to complete – by tumor, line of treatment etc. It also allows to benchmark approval timelines between companies and make comparisons between US and EU approval timelines.
The Pipeline section provides a “big picture” view of all ongoing trials for a given compound and displays the total number of patients that were or will be recruited. By selecting a tumor and a line of treatment, for example, a quick overview can be obtained on the compounds and number of trials ongoing in a given indication. This also allows to foresee which players are likely to dominate certain therapeutic areas in the future. Selecting a company allows to get a rapid overview over the company pipeline, number of trials and patient numbers. Each aggregated search result (e.g. 5 trial results in a given tumor) can be further analyzed by clicking on the result which allows to analyzed the trials individually in a new window that is being opened.
The Landscape section provides and automated view of the industry pipeline per tumor worldwide. The Landscape section focuses on potential label enabling trials that will generate results in the future or that have yielded positive results recently. The results can be further refined by using filters such as line of treatment, Immuno-Oncology, study sponsor etc. In order to be able to generate an automated and as accurate as possible view of the complete pharma and biotech development efforts worldwide, the following rules were defined: 1. For each drug only the most advanced development stage is shown (e.g. if a drug is being tested in 3 phase I and 2 phase II trials then only the 2 phase II trials will be displayed). For approved drugs the trials that led to the corresponding approval as well as ongoing phase III trials are displayed (but not phase I or II), 2. Trials that generated positive results more than 18 months ago are not included (it is assumed that these trials are not of relevance anymore), 3. Negative trials are not included (they will not result in a regulatory approval), 4. Phase III trials that are not expected to lead to a regulatory filing are excluded from the analysis.
This section lists all trials that will start in the future. These trials can be grouped into 3 categories: 1. Phase III trials that have been announced and are not yet published online. Some companies disclose their phase III trials plans months before the trial is posted online. We also include our estimate about the trial duration and filing timelines based on similar sized studies that were conducted in the past (this information is gathered from the section “Key timelines”). Once we have more information from the company regarding trial duration and filing timelines we update the information accordingly, 2. Trials that have been published online but recruitment has not yet started, 3. Preclinical projects.
This section displays the trials in chronological order. The trials that appear at the top of the table are the ones that were most recently published on clinicaltrials.gov (usually on the same day or the following business day after they first appear on clinicaltrials.gov). Every day approximately 10-15 new Oncology trials are published on clinicaltrials.gov and subsequently included in our database. The last column in the table shows the month and year where the trial was published online. The section “Latest trials” allows to sort quickly through latest trials published by a competitor, identify the latest phase III trials that were initiated, search for the latest trials by a molecular target and much more
This section allows to quickly identify the key registrational trials that are expected to readout in the coming months. As in all other sections the search engine and filters allow to quickly focus on areas of special interest (by tumor, company, molecular target, line of treatment etc.). The data readout timelines are based on different sources: 1. We always check data readout timelines provided by the companies on clinicaltrials.gov and use them as a potential source, 2. When available we use data readout timelines provided by the companies. Example: a company guides for data readout in H2 2020. In that case we usually use September 2020 as a data readout estimate, 3. Our large database allows us to make our own estimates on data readout timelines based on similar studies performed in the same indication. In some cases, we use our own estimates as opposed to the timelines on clincialtrials.gov. This is especially the case if we consider the timelines reported on clinicaltrials.gov to be very conservative