From better patient selection to optimal approval rates and higher drug pricing.
A tremendous effort has to be made before clinical trials on humans are initiated for a
With our unique approach and our expertise in this field, we will help you to significantly improve the approval rate, reduce the costs and achieve higher prices.
The likelihood to bring a new drug entering Phase 1 to the market differs significantly in the various
disease areas, from 26.1 % at the high end for hematology to 5.1% at the low end for
oncology and with an average of 9.6% for all disease areas.
The sobering statistic is that out of ten drug candidates entering phase 1 only one drug gets approval. Three out of four failing drug candidates fail due to lack of efficacy or safety. Both reasons could be eliminated by:
Realizing an intelligent patient selection strategy as a fundamental component of each
clinical trial guarantees to maximize the likelihood for approval of a new drug to up to
Figure 1 illustrates the extreme increase of approvals enabled by OakLabs' unique strategy to identify responders in comparison to conventional clinical trials.
A companion drug that is capable of identifying strong responders of a specific therapy enables higher pricing and therefore fully compensates the drawback of a reduced market share.
OakLabs' solution starts with the development of complex biomarker signatures for patient selection based on OMICs data. OakLabs' services comprise the acquisition of OMICs data such as RNA, protein and metabolite profiling required for biomarker development as well as the molecular testing of each patient for presence of the responder signature.
Figure 2 demonstrates how the clinical trial workflow changes with OakLabs' contribution.
Table A summarizes the costs for phase 2 of a potential drug for a gastrointenstinal therapeutic area. Based on the stated responder rate, the improved patient selection by the developed biomarker signature as well as the overall cost per patient in the clinical study, the following savings in phase 2 and 3 were calculated:
|Total cost of phase 2||16,000,000 USD|
|Number of patients||400 patients|
|Overall patient cost in phase 2||7,200,000 USD||Benefits|
|Increased responder rate with biomarker signature for patient selection||60 -> 95 %|
|No. of excluded patients based on biomarker signature||140 patients|
|Total budget saved||6,500,000 USD|
|Total time saved||8 months|
Though OakLabs' strategy and services require some inital effort, the resulting biomarker signatures guarantee significant savings in the whole subsequent progress and support higher drug prices on the market.
You are a CRO or pharmaceutical sponsor and would like to receive an individualized calculation of the benefits of cooperating with us?
Just about 5% of clinical phase transitions incorporate a selection biomarker as inclusion or exclusion criterion. Though the selection is usually based on a single biomarker, the selection biomarker improves the likelihood of approval from Phase I to 26% compared to less than 10% without selection biomarker.
A complex biomarker signature will further increase the likelihood of approval to even 68% and at the same time reduce the overall patient costs. In addition, it will accelerate the successful completion of the clinical trial and facilitate to demand higher drug prices on the the market.
By using machine learning algorithms, OakLabs achieves significant improvements of the accuracy of complex biomarker signatures. The representative ROC curve in fig. 3 illustrates the superiority of the protein type biomarker signature of eight analytes after OakLabs' support.
Out of the broad range of benefits, table B contrasts typical savings resulting from OakLabs' biomarker signature based patient selection compared to a conventional clinical study design as well as to patient selection based on a single biomarker. The performance parameters sensitivity and specificity refer to the colored data points of the ROC curves in figure 3.
|Patient selection||Conventional||Traditional Biomarker||OakLabs's Biomarker Signature|
|Sensitivity of responder selection||/||90%||95%|
|Specificity of responder selection||/||60%||94%|
|Overall number of patients to recruit||1,500||1,690||1,375|
|No. of patients to include based on biomarker test||/||990||945|
|No. of patients to exclude based on biomarker test||/||700||430|
|Total patient cost of phase 3||30,000,000 USD||23,000,000 USD||21,050,000 USD|
Benefits of OakLabs' biomarker signature
There is a broad range of data you can acquire from patients including including proteins, mRNA, miRNA, proteins, DNA methylation, metabolites or SNPs in various sample types like plasma, serum, urine, liquore, biopsies or facies. Which sample type and biomarker type is most suitable strongly depends on the individual clinical trial. The table below gives a brief overview of regular settings we support/accompany. Nonetheless, we profoundly evaluate each project individually and therefore ensure to proceed with the best strategy.
|Technology for signature development||Antibody Microarray Platform||DNA Microarray Platform||LCMS and GCMS|
|No. of detected analytes||> 900 proteins||> 30,000 mRNAs||> 1,000|
|Analytes||Broad set of different protein classes as well as relevant pathways in biomedical studies||Genome-wide gene expression analysis||~30% known and ~70% unknown metabolites (polor and lipid metabolites)|
|Compatible sample types (starting material)||Plasma, Serum, Urine, Liquor||PBMCs, Tissue samples||Plasma, Serum, Urine, Liquor, Facies|
|CDx translation technology||ELISA||RT-qPCR or micrarray-based||LCMS / GCMS / Other (depends on particular metabolites in biomarker signature)|
Rapid translation to CDx
broad equipment compatibility to run CDx in labs
|Rapid and cost-efficient translation to CDx
flexible technology depending on marker set size (RT-qPCR or microarray)
|Diverse technology options for translation to CDx|