Data Validity and Authenticity before CNIPA and Court

by Jiaqian HU, Ying YU (Shanghai Patent & Trademark Law Office, LLC. – China)

For patents or patent applications directed to chemicals, pharmaceuticals and other like subject matter, experimental data may be essential to overcome various objections, such as to answer enablement challenges or to prove an unexpected technical effect to support patentability. However, sometimes errors in data are found during litigation, or even prosecution, leading to validity or even authenticity doubts.

I.Patents being invalidated for faulty experiment data

The Beijing Higher People’s Court made a judgment of affirmation in Patent Reexamination Board vs. Sihuan Pharm Co. on December 24, 2018, affirming the Board’s decision of invalidity of Patent No. 200910176994.1 owned by Sihuan Pharm Co.. Particularly, the Court ruled against the appellant by not acknowledging validity and authenticity of the insecticidal activity data as recorded in the patent.

Meanwhile, in the decision of “(2016) Jing. 73. Admin. First. 6067″ (translated), the Beijing Intellectual Property Court also ruled against Sihuan Pharm Co. in another patent of this owner, No. 201110006357.7 (‘357 patent herein below), affirming the Board’s decision of invalidity and noting that the data of effects as recorded in the patent are defective in validity and authenticity.

In particular, the Court commented on the data as saying that Example 5 in the ‘357 patent does not specify the grouping of animals, the mode of administration or the procedure for calculation of the LD50 values, and moreover, the frequency of dosing is found obviously contradictory to the definition of LD50 as known in the art; while in Examples 6 and 7, there are mistakes of transcription in the data, which makes the data incomprehensible in context.

During trial, the patent owner failed to present either the original records of data or a convincing validation via explanation. Finally, in the decision, the Court is quoted as saying that for pharmaceutical patents, experimental data are not only required to be disclosed adequately in the specification but must also be completely accurate, and this is a manifestation of quid pro quo in the doctrine of “disclosure for protection” in this field. The Court further notes that insufficient or inaccurate data, as well as a conclusion drawn thereby, are not effective in proving fulfillment of the invention to solve the objective problems.

II.Similar cases in Examination and Reexamination in the CNIPA

As far as we can see, the Examiners are more often looking into validity and authenticity of experimental data in applications, especially in the fields of pharmaceuticals and agriculture.

For instance, in the decision No. 1F216463, the Board of Reexamination concluded that in a series of applications filed by the same applicant, the data are incredible or unauthentic when formulations of different active ingredients, recipients and dosages illogically reported the same result in different applications. The Board decided that in view of the doubt in the data validity and credibility, the applicant’s argument of fulfillment shall not be sustained.

In some cases, the Examiners investigate data in a series of inter-related applications to see whether there exist illogical defects in data among various cases. In one case, the Examiner doubted the validity and authenticity of the data in a series of related applications when finding that tests of the same agent against the same damage on the same plant species reported dramatically different results between applications. In another case, the Examiner negated enablement, asserting that the claimed dosage form was unobtainable according to common knowledge in the art.

As seen, faulty data even in just one test may jeopardize the whole patent or application, or even more related patents or application, based on doubts with respect to the data validity or authenticity.


In light of the new trends of data inquiry, we would recommend taking details more seriously, such as steps and conditions of experiments, methods of data analysis and treatment, for which the disclosure needs to be clear and complete. For drafting, generic qualitative assertions are less advisable, while quantitative data of performance and results are more desirable. Moreover, before filing, make sure that all the data in the application have been checked to eliminate at least obvious errors from the view of techniques. For a series of patent applications of the same applicant, more attention is called for on coherence between applications to avoid conflicts and inconsistencies. What’s more, it is always advisable for inventors/applicants to keep original records of experiments and data in case of challenges and doubts.