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Applied DNA Secures $1.0+ Million in COVID-19 Surveillance Testing Annualized Revenue, Builds Sales Pipeline for Test Kit and Testing-as-a-Service

– Announces Completion of Initial New York State Department of Health Inspection of Clinical Lab Subsidiary –

Applied DNA Sciences, Inc. (NASDAQ: APDN) (“Applied DNA” or the “Company”), a leader in Polymerase Chain Reaction (PCR)-based DNA manufacturing that enables in vitro diagnostics, pre-clinical nucleic acid-based therapeutic drug candidates, supply chain security, anti-counterfeiting, and anti-theft technology, announced that Applied DNA Clinical Laboratories, LLC (“ADCL”), its wholly-owned subsidiary, has secured COVID-19 surveillance testing contracts under its testing-as-a-service (“TaaS”) offering that are estimated to generate more than $1.0 million in total annualized revenue beginning October 1, 2020. The Company’s surveillance testing revenue expectation is contingent on full-term participation by TaaS customers, including:

  • Private schools based in Long-Island, N.Y., including Harbor Country Day School. Education customers comprise the bulk of the Company’s current testing volume;

  • Several New York State-based small enterprises and private clients.

Unlike diagnostic testing, which looks for the occurrence of COVID-19 at the individual level, surveillance testing looks for infection within a defined population or community and can be used for making health management decisions at the population level. Surveillance testing does not require a prescription. In surveillance testing, pooled test results are returned to the sponsoring organization in the aggregate, not directly to the individual, and may be performed without CLIA certification.

Concurrently, the Company is executing on a sales and marketing strategy to build a pipeline of LineaTM COVID-19 Diagnostic Assay Kit (“Assay Kit”) and TaaS opportunities through:

  • Outreach to independent and hospital laboratories in COVID-19 hotspots nationally and regionally to offer an additional diagnostic kit supply line;

  • Outreach to local laboratories to construct a reference laboratory relationship for overflow testing;

  • Deployment of testing at Stony Brook University in accordance with a recently signed Master Services Agreement.

“Our capacity to perform COVID-19 surveillance testing is grounded in self-collection saliva kits and anterior nasal swab kits that are intuitive to use, a highly sensitive PCR-based Assay Kit that can detect as little as one copy of the SARS-CoV-2 genome per microliter in an individual saliva sample, and a high-throughput surveillance testing lab that can return testing results within 24 hours and often on the same day as sampling. When deployed as part of a consistent and ongoing surveillance testing regime, we believe our Assay Kit can help our clients to detect the virus before its median incubation time of 4 to 5 days from exposure to symptom-onset1. Being able to identify infections early and in a cost-efficient and rapid manner is how surveillance testing gets workers back to work and students back to school,” said Dr. James A. Hayward, president and CEO.

“We are beginning to see the first fruits of our Assay Kit and TaaS sales and marketing efforts translate into revenue,” concluded Dr. Hayward. “As we continue to expand our sales pipeline of Assay Kit and surveillance testing opportunities, we believe these efforts can serve as a potentially material driver of our growth supplemented by diagnostic customer testing upon receipt of CLEP-CLIA certification.”

An Unprotected Analytics Pipeline Undermines The Value Of Data

Ameesh Divatia is co-Founder & CEO of Baffle, Inc., with a proven track record of turning innovative ideas into successful businesses.

Some estimate that 90% of the world’s data has been produced in the past two years alone. This proverbial tidal wave of information positions businesses to inform decisions that optimize operations, attract and retain customers, and create significant market differentiation. The challenge is how to make sense of data in multiple formats that emanate from disparate sources.

For data to provide value, it must flow through what is referred to as the analytics pipeline: the infrastructure used to collect, store and process data in an IT environment. In the analytics pipeline, unstructured data — such as emails, Excel spreadsheets, Word documents, presentations, instant messages, photos, audio and video — enters “upstream.” As data moves “downstream” toward the end of the pipeline, it is cleansed, organized and analyzed via predictive analytics and machine learning. 

At this point, data is at its peak value and, consequently, is more attractive to hackers. For this reason, data protection must be an integral part of the data analytics pipeline to prevent incidents that can offset the many benefits that analyzed data can provide. 

Cloud Storage And Data Sharing Risk

Before exploring how to secure the analytics pipeline, let’s look at two important business trends that will benefit from such protections: cloud storage and data sharing.

The cloud’s limitless storage capabilities are prompting enterprises to migrate data from on-premises environments, store it in data lakes and extract useful data into warehouses for analysis. Downstream data stored in the cloud is a target for criminals due to its high value and because it is often not protected properly. Many organizations relax security controls to momentarily enable easier access, but forget to restore the protection that it requires. 

Further, Palo Alto Networks (via Help Net Security) found that 43% of cloud storage is left unencrypted, even though cloud providers encrypt those buckets by default. This is an alarming statistic for organizations incorporating the cloud as part of their analytics pipelines — especially for those tasked with complying with regulations like GDPR and CCPA, with almost half of their crown jewels ready to be stolen.

Risk of exposure is further compounded when data moves outside of an organization. Many enterprises rely on data sharing as an integral part of their operations or in collaboration with other organizations to solve problems and gain insight. The Ponemon Institute found that, on average, companies share data with 583 third parties. The same study crystallized the risk of this practice, with 61% of U.S. CISOs experiencing data leakage via a third party. 

This creates a conundrum: Stop sharing data, or share it in an insecure manner. Without a secure analytics pipeline, these two critical elements now represent unnecessary risk.

Securing Data Throughout The Pipeline

Security controls for the analytics pipeline can be categorized into two groups: visibility and entitlement. According to Gartner, visibility pertains to implementing “controls that remove ambiguity