In the past year, Aeonian Biotech has provided consultation services to biotech companies for market assessments, technical writing, overviews of portals, and to improve antibody presentation. We started this mission at the back of the reported reproducibility crisis (Freedman 2017), when the reliability of research antibodies became an issue (Baker 2015, Weller 2016, Freedman 2016). Based on raised concerns about finding fit-for-purpose antibodies in the market (Rizner et al 2016, Goodman 2018), with the risk of buying the same antibody from different sources (Voskuil 2014), we decided to offer our services to identify the best candidates in the market knowing who the original manufacturers are and knowing what criteria to use for meeting the specific requirements of the customers.
In addition, we have now started to offer high quality antibodies ourselves. We primarily concentrate on monoclonal antibodies with a preference for recombinant (sequence-defined) antibodies (Bradbury et al 2018). Each one of them have been thoroughly vetted and been provided with the Aeonian Rating®. Any rating under the 70 will not appear on our catalogue.
Our proprietary Aeonian Rating® is based on the antibody’s formulation, the clonality, the disclosure of the epitope, evidence of specificity, and evidence of fitness for specific species and immunoassays (See Our Vision). Thus, the rating combines the specifics of the product that are independent on its performance, with performance-related specifics (Voskuil, 2017). An antibody can be rated maximally 100 when it meets all Aeonian quality requirements. The number of fit applications has no influence on this rating, but the quality of evidence has. A monoclonal antibody demonstrated fit in multiple applications but offered as a culture supernatant may not be rated as high as once such antibody is offered as a purified product (offered at a given concentration and amount in ug or mg). An antibody will reach AR100 when it is a recombinant monoclonal antibody with known epitope, with convincing evidence of specificity, and with evidence of at least one piece of data to demonstrate its fitness in one application, say Western blot. The specificity may have been tested in a protein array containing closely related other proteins next to the intended protein it reacts to and showing no cross-reactivity. This latter type of specificity evidence is presented in most of our products. If not, comparisons of wild type with knockout or with non-expressing tissue or cell types are required.
We will not report cross-reactivity to a species until there is data to demonstrate it. Likewise, when an antibody was claimed fit for flow cytometry, but there is only Western blot or Immunohistochemistry data presented, the flow cytometry will not be reported as an application, until proven fit by publication. Immunohistochemistry on wrong tissues will be disregarded. For example, an antibody to a brain protein may have been tested in lung or liver slides. Such data will not be presented and IHC will not be reported to be a positively tested application.
In addition to the Aeonian Rating®, we add the Research Reagent Identity (RRID) to our product pages. This will help identifying the right reagent once it has been used and recorded in future publications and others need to reproduce the reported results in their own ways. The RRID is becoming increasingly appreciated as a new standard enabling automated recognition of the right reagents in publications (Bandrowski et al 2018).
It is our mission to elevate the standard of quality in the biomedical research by our contribution to identifying the right reagents in the most cost-effective way. We hope that this will enhance the reproducibility of research to escalate progress in finding new diagnostics and therapies.
Freedman et al (2017) Reproducibility2020: Progress and priorities. F1000Res. 6: 604.
Baker (2015) Reproducibility crisis: blame it on the antibodies, Nature. 521(7552): 274-6.
Weller (2016) Quality Issues of Research Antibodies. Analytical Chemistry Insights 11: 21–27
Freedman (2016) GBSI Workshop Report: Antibody Validation: Strategies, Policies, and Practices. Reference Source
Rizner et al (2016) Recommendations for description and validation of antibodies for research use. J Steroid Biochem Mol Biol 156:40-42.
Goodman (2018) The path to VICTORy – A beginner’s guide to success using commercial research antibodies. J Cell Sci 131(10):jcs216416
Voskuil (2014) Commercial antibodies and their validation, F1000Res. 3:232.
Bradbury et al (2018) When monoclonal antibodies are not monospecific: Hybridomas frequently express additional functional variable regions. MAbs. 10(4):539-546.
Voskuil (2017) The challenges with the validation of research antibodies. F1000Res 6:161.
Bandrowski et al (2018) The Resource Identification Initiative: A cultural shift in publishing. Neuroinformatics 14(2):169-82.