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Intec Pharma Reports Second Quarter 2019 Financial Results and Business Update



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Intec Pharma Ltd. (NASDAQ: NTEC) (“Intec” or “the Company”) today announces financial results for the three and six months ended June 30, 2019.

Highlights of the second quarter 2019 and recent weeks include:

  • Completed the qualification studies for the commercial scale manufacture of Accordion Pill®-Carbidopa/Levodopa (AP-CD/LD) with LTS LohmanTherapie-Systeme;
  • Announced topline results from the Company’s pivotal Phase 3 trial (the ACCORDANCE trial) evaluating the safety and efficacy of the AP-CD/LD compared with immediate release CD/LD (IR-CD/LD; Sinemet®) as a treatment for the symptoms of advanced Parkinson’s disease (PD), reporting that AP-CD/LD provided treatment for Parkinson’s disease symptoms but did not demonstrate statistically superiority to IR-CD/LD in terms of reduction in OFF time from baseline under the conditions established in the protocol;
  • Completed the pharmacokinetic (PK) study of the custom-designed AP developed for a proprietary compound under the previously announced feasibility and option agreement with Novartis Pharmaceuticals;
  • Entered into an agreement with Merck to explore using the AP platform for an undisclosed development program;
  • Published a review highlighting the benefits of the AP oral drug delivery platform in the peer-reviewed journal, Therapeutic Delivery;
  • Published the results from an earlier Phase 2 clinical study of the AP-CD/LD in PD patients in the peer-reviewed journal, Parkinsonism and Related Disorders;
  • Presented data from the PK study of AP-CD/LD 50/500 mg TID in a poster at the XXIV World Congress on Parkinson’s Disease and Related Disorders; and
  • Granted European patent titled, “Delivery Device for Oral Intake of an Agent,” which covers Intec’s gastro-retentive drug delivery device with perforated external film.

Management Commentary

“We were very disappointed that the ACCORDANCE study did not meet its target endpoints. In our preliminary review of the top-line data, we noted sub-sets of patients that performed particularly well, showing meaningful reduction in OFF time compared with IR-CD/LD. Based on our preliminary review, we believe we may not have been able to administer enough LD to certain patients as it was agreed with the U.S. Food and Drug Administration (FDA) that the maximum dose would be three APs per day. Given the long-term safety profile established by this trial, we believe this limitation should be removed and that this could present a method of providing additional LD to those patients who need it. We believe the on-going analyses of this study will lead to an improved understanding of what will be required in future studies to generate approvable clinical data with the AP delivery platform in PD,” stated Jeffrey A. Meckler, Vice Chairman and Chief Executive Officer of Intec Pharma.

“During the second quarter, we made significant progress advancing and expanding our partner-sponsored programs.  We are excited to have successfully completed the PK study for our custom-designed AP for Novartis’ proprietary compound and are looking forward to advancing this program into potential partnership discussions.  This partnership holds significant promise as the market opportunity for this proprietary compound is in excess of $1 billion. In addition, we entered into a research collaboration with Merck for the development of a custom-designed AP for one of Merck’s proprietary compounds and are now initiating the design and construction of this new AP for this very promising program.

“We continue to make progress refining the AP for our cannabis program and hope to advance our proprietary AP containing synthetic tetrahydrocannabinol (AP-THC), one of the primary cannabinoids contained in cannabis, into a new PK study next year. The Accordion Pill has the potential to address several major drawbacks of current methods of use and treatment with cannabis and cannabinoids, such as short duration of effect, delayed onset, variability of exposure, variable potency batch to batch, variability of the administered dose and adverse events that correlate with rate of rise and peak levels. Given the known analgesic properties of cannabinoids, we remain enthusiastic about the potential for these programs and believe our AP-cannabinoids will be applicable to a variety of pain indications.

“While the ACCORDANCE results were not what we expected, we continue to believe in the potential of the AP platform. Toward that end, we plan to seek to move forward with a commercial agreement with Novartis. In addition, once we obtain the final data from our ACCORDANCE study, we plan to look for ways to advance this program forward, whether on our own or through a potential partnership. In tandem, we plan to continue to build our AP drug delivery platform with the addition of both partner-sponsored R&D programs, such as Novartis and Merck, and through internally led drug reformulation programs, such as our cannabis program in pain indications. We believe this strategy provides the best opportunities for both short- and long-term growth,” concluded Mr. Meckler.

Financial Highlights for the Three and Six Months Ended June 30, 2019

Research and development expenses, net, for the three-month period ended June 30, 2019 were approximately $7.9 million, a decrease of approximately $500,000, or 6%, compared with approximately $8.4 million for the second quarter of 2018. Research and development expenses, net, for the six-month period ended June 30, 2019 amounted to approximately $16.4 million, a decrease of approximately $900,000, or 5%, compared with approximately $17.3 million in the six-month period ended June 30, 2018. The decrease in both periods was primarily due to a decrease in expenses related to our ACCORDANCE study and open label extension study, offset by an increase in expenses related to the scale up activities for the commercial-scale production capabilities for AP-CD/LD at LTS.

General and administrative expenses for the three-month period ended June 30, 2019 were approximately $2.1 million, a decrease of approximately $100,000 or 5%, compared with approximately $2.2 million in the three-month period ended June 30, 2018.  General and administrative expenses for the six-month period ended June 30, 2019 amounted to approximately $4.3 million, an increase of approximately $200,000, or 5%, compared with approximately $4.1 million in the six-month period ended June 30, 2018. The increase in the six-month period was primarily related to the increase in payroll and related expenses mainly due to an increase in headcount and salary raises and insurance expenses, offset by a decrease in professional services.

Net loss for the three-month period ended June 30, 2019 was approximately $10.0 million, compared with a net loss of $11.0 million in the prior year’s second quarter.  Net loss for the six-month period ended June 30, 2019 was $20.7 millioncompared with $21.8 million during the six-month period ended June 30, 2018.

Loss per ordinary share for the three-month period ended June 30, 2019 was $0.30 compared with a loss per ordinary share of $0.34 for the three-month period ended June 30, 2018. Loss per ordinary share for the six-month period ended June 30, 2019 was $0.62 compared with a loss per ordinary share of $0.75 for the six-month period ended June 30, 2018.

As of June 30, 2019, the Company had cash and cash equivalents and marketable securities of approximately $21.6 million compared with approximately $40.6 million at December 31, 2018.

Net cash used in operating activities during the six-month period ended June 30, 2019 was approximately $17.7 millioncompared with net cash used in operating activities of approximately $19.9 million during the six-month period ended June 30, 2018. This decrease resulted primarily from the decrease in the net loss for the period in the amount of $1.1 million and from changes in operating assets and liabilities items of approximately $300,000.

The Company had negative cash flow from investing activities of approximately $1.0 million during the six-month period ended June 30, 2019 compared to negative cash flow from investing activities of approximately $4.3 million during the six-month period ended June 30, 2018. This decrease resulted primarily from a decrease in purchase of property and equipment in the amount of approximately $2.5 million, an increase in proceeds from the disposal of marketable securities in the amount of approximately $576,000 and a decrease of approximately $261,000 in investment in other assets related to the establishment of the commercial scale production capabilities for AP-CD/LD at LTS.

Net cash provided by financing activities during the six-month period ended June 30, 2019 was approximately $268,000, which was provided by the proceeds from the exercise of options by employees. Net cash provided by financing activities for the six months ended June 30, 2018 was approximately $35.0 million which was mainly provided by funds received from our April 2018 public offering of ordinary shares.


SOURCE Intec Pharma Ltd.


Strainprint™ Technologies Welcomes Organic Medical Cannabis Producer to Growing List of Subscribers



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Strainprint™ Technologies Ltd, the leader in cannabis data and analytics is pleased to expand their nation-wide coverage with the addition of Stewart Farms.

Stewart Farms is a late-stage applicant headquartered in Alberta that is building a 100,000 sq. ft. vertical aquaponics farm in Saint StephensNew Brunswick. They will be utilizing automation, vertical farming, and land-based aquaculture to produce medical grade organic cannabis for both recreational and medical markets in Canada. All of their products will be free of herbicides, pesticides and synthetic nutrients. At full capacity, they will reach more than 10,000 kgs per year of organically farmed cannabis and more than 200,000 kgs of organic tilapia.

Stewart Farms’ long term vision is to deliver tools and products to support  future customers and patients during their health and wellness journeys. “Through our partnership with Strainprint we gain direct access to their incomparable data and analytics tools. This will aid us in educating a wider audience on the medical benefits and best practices of cannabis-based medicine,” said Tanner Stewart, Co-founder & CEO of Stewart Farms. “We know our customers are looking to consume more than dried cannabis. We know Canadians of all legal ages are trying to sort through their personal engagement with cannabis as a medicine. What we want to know, on an ongoing basis, is what is and is not working for people. Strainprint’s patient-led data services will give us the insight needed to create custom products and further understand the benefits of our existing products. Finally, our goal is to partner with companies and teams that truly have people’s best interest at heart. Caring about a patient’s success is what makes up the core of the Strainprint team. We couldn’t be happier to move forward with them at our side.”

Stewart Farms will access the Strainprint Analytics web platform, the most sophisticated cannabis analytics platform available to improve product development. Strainprint Analytics is built on top of the largest and most granular scientific data set of its kind in the world, with more than 1.3 million anonymized, patient reported medical cannabis outcomes and more than 65 million data points on strain efficacy.

“We’re thrilled to provide our real-time, crowd sourced data to an environmentally conscious company that uses innovative, cutting edge farming technology to produce top-tier medical cannabis,” said Strainprint CEO, Andrew Muroff. “Our organizations are equally committed to improving lives using cannabis therapy, and our shared core motivation is to provide guidance and support to help cannabis patients achieve their health goals.”


SOURCE Strainprint Technologies Ltd.

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Field Trip Ventures Inc. Retains KCSA Strategic Communications as Public Relations Counsel



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Greenery Map, the world’s first and only cannabis search engine to allow users to search for cannabis products based on their desired mood, medicinal use, and method of consumption, is now offering users – both businesses and consumers – the opportunity to register and connect to the app in an entirely mobile way. Previously, businesses were required to access from a desktop in order to manage accounts and connect to the inventory API system, but that road block has been removed, allowing for an entirely mobile experience through the Greenery Map app.

App users turn to Greenery Map to help them decide on the strain of Cannabis and product that is right for them depending on their desired mood or medicinal effect. Following the matching, consumers are given a detailed history and description of the strain so that they can make educated purchases, cutting down on time that budtenders need to spend with patrons and speeding up the purchase process. Consumers can then see all of the ways to purchase said product, including the nearby dispensaries that have it in stock, online options, and even delivery options through the app. Greenery Map fully integrates with a dispensary’s inventory API system to update in real-time and give consumers real-time information on dispensary stock for the item they are looking for. The Greenery Map system also provides cannabis businesses in both the B2B and B2C sectors a private database to share and sell information and products. For Cannabis businesses, Greenery Map also offers the opportunity to open bank and merchant accounts through their partnership with PayHouse Consulting Group.


SOURCE Greenery Map

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WeBank, IBM and Other Organizations Jointly Held the 1st International Workshop on Federated Machine Learning in conjunction with IJCAI 2019



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Once a concept, AI is now ushering in a key stage of application. What’s the solution to the data silos among businesses? Given the enhanced regulation on data at home and abroad, what’s the solution to data privacy and security concerns? What’s the status quo of Federated Machine Learning and how to establish an ecosystem for FML in the future?

WeBank, IBM and other organizations jointly held the 1st International Workshop on Federated Machine Learning for User Privacy and Data Confidentiality (FML’19) in conjunction with the 28th International Joint Conference on Artificial Intelligence (IJCAI-19) on Aug. 12, 2019, to further discussion on these issues.

President of IJCAI, Chair of FML Steering Committee, Chief AI Officer of WeBank Professor Qiang Yang delivered opening remarks at the workshop. Dr. Shahrokh Daijavad from IBM and Dr. Jakub Konečný from Google presented keynote addresses. In the panel discussion, top scholars from WeBank, Bar-Ilan University, IBM, Squirrel AI, Google, Huawei, Clustar, Sinovation Ventures and many other renowned enterprises and universities shared and discussed their findings and experience in FML as an emerging AI technology.

This workshop received 40 papers, of which 12 were presented during the workshop, 19 presented via poster. Awards include Best Theory Paper Award, Best Application Paper Award, Best Student Paper Award, Best Presentation Award. Selected high quality papers will be invited for publication in a special issue in the IEEE Intelligent Systems journal. All these attracted numerous scholars to engage in discussions and join efforts for building the FML ecosystem.

Experts from IBM and Google Share Groundbreaking Findings with a Focus on the Theory and Application of FML

Privacy and security are becoming a key concern in our digital age. On 25th May last year, the implementation of General Data Protection Regulation (GDPR) by the EU, the toughest Act on data privacy protection, stressed that user data collection must be open and transparent. A series of laws and regulations from China and overseas also pose new challenges to the traditional way of handling data and model for cooperation. Seeking ways for AI to adapt to this new reality became top priority, a demand that led to this workshop on FML.

A wealth of solutions and breakthroughs were shared by Dr. Shahrokh Daijavad from IBM and Dr. Jakub Konečný from Google in their speech on FML.

Besides how FML can help tackle challenges in the business world, Dr. Shahrokh Daijavad also shared the concept of Fusion AI, which means to train models on widely distributed data sets, but fuse them to produce one equivalent to what centralized training would yield. “Unlike traditional machine learning, in Fusion AI, model parameters are shared and data is not transferred, which makes Fusion AI model better than models that moving data centrally.” Given the widely distributed data, the development of Fusion AI and FML became ever important and imminent.

“FML enables machine learning engineers and data scientists to work productively with decentralized data with privacy by default,” said Dr. Jakub Konečný from Google. He also shared with us how FML works and its use cases at Google. In the case of Gboard, as on-device data is privacy sensitive or large or is more relevant than server-side proxy data, and labels can be inferred naturally via user interaction, the application of Federated RNN compared to prior n-gram model can increase the accuracy of next-word prediction by 24%, and the click rate of prediction strip by 10%.

Major Figure Panelists Discuss the Way Ahead for FML

The moderator of the panel discussion, AI Principal Scientist of WeBank Dr. Lixin Fan joined panelists including Professor Benny Pinkas from Bar-Ilan University, Dr. Shahrokh Daijavad of IBM Academy of Technology, Chief Architect of Squirrel AI Dr. Richard Tong, Research Scientist of Google Dr. Jakub Konečný, Dr. Baofeng Zhang from CTO Office of CBG Software in Huawei, Executive VP of Clustar Dr. Junxue Zhang, VP of AI Institute in Sinovation Ventures Dr. Ji Feng and other experts in a host of in-depth exchanges with attendees, to shed light on the way ahead for FML.

Experts shared thoughts in the panel discussion on questions including but not limited to: How to meet the security and compliance requirements? Is there a way to extend the value of data while observing user privacy and data security? Given the classic trade-off between data regulation and development of AI, how to achieve the long-term goal of establishing a stable and win-win business ecosystem?

List of Award-Winners

Best Theory Paper Award, Best Application Paper Award, Best Student Paper Award and Best Presentation Award selected by all attendees were announced at the closing of the workshop.

Best Theory Paper Award: 
Preserving User Privacy for Machine Learning: Local Differential Privacy or Federated Machine Learning? By Huadi Zheng, Haibo Hu & Ziyang Han;

Best Application Paper Award: 
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare. By Yiqiang ChenJindong WangChaohui YuWen Gao & Xin Qin;

Best Student Paper Award: 
Quantifying the Performance of Federated Transfer Learning. By Qinghe JingWeiyan Wang, Junxue Zhang, Han Tian & Kai Chen;

Best Presentation Award: 
Federated Generative Privacy. By Aleksei Triastcyn and Boi Faltings.

President of IJCAI, Chief AI Officer of WeBank Professor Qiang Yang, Chief Architect of Squirrel AI Dr. Richard TongandVP of AI Institute in Sinovation Ventures Dr. Ji Feng presented the awards.

“The mission of this International Federated Machine Learning Workshop is to facilitate further understanding in the academia, business community as well as legal and regulatory institutions by promoting the establishment of FML ecosystem in the hope that more businesses will join and build a platform for students aspired to work in FML to find research teams that suit them,” said Professor Qiang Yang.

Held Aug. 10-16, 2019 in Macao, China, IJCAI-19 is one of the leading International Academic Conference on AI, attracting over 3000 AI research personnel and experts. The 1st International Workshop on Federated Machine Learning (FML’19) was a highlight for experts joining this event. Visionaries in the academia and industrial sector expressed the willingness to be part of the effort for academic research, application of FML in the future, and the development and boom of AI ecosystem.

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