© Digitalbiopharm Ltd All rights reserved. Distributed computing platform for making breakthrough biomedical technologies © Digitalbiopharm Ltd All rights reserved.

The problem: New drugs can cost $1B or more to develop and require years to gain approval. Companies must spend large amounts of money to develop and test new compounds. Once promising compounds are identified, testing them to obtain government approval takes many years: 2 There is a need for new medicines especially antibiotics, antivirals & cancer treatments High costs (sometimes above $1B) and long time periods hinder or discourage development of new medicines Experimentally it is impossible to study virtual chemical areas (compounds, which may be a drug, but are not synthesized yet – these is no less that several hundreds of billions of such compounds available right now and will be available in the future) Difficulty to create multi-targeting (polypharmacological) drugs using experimental methods

© Digitalbiopharm Ltd All rights reserved. Current Solutions Experimental: Biological experiments (high-throughput screening, DNA-encoded libraries) Computational Supercomputing clusters rental/purchase Сloud computing rental/purchase Shortcomings: expensive and long These methods are more expensive in comparison to our solution (we beat everyone by costs) Some of them will take more time (high-throughput screening) for less number of molecules Experimental methods can handle only synthesized spaces of compounds (not virtual chemical spaces). In case of DNA-encoded libraries the limits are imposed by combinatorial chemistry capabilities Not easy to scalability Lack of the community involvement and crowdsourcing 3

Harness the power of millions of computational devices (PC, smartphones, GPUs, Clusters) to identify and evaluate new compounds outside the constraints of traditional drug development. Big computational resources at very low cost. Volunteer computing enables enormous computing power, costs very little. 4 Our Solution: © Digitalbiopharm Ltd All rights reserved.

SOFTWARE Project parts Description of the product and project technology Product is the platform for distributed computing that uses volunteer computer resources for new drugs development. Server Client BOINC is the platform with open code that provides interaction between client and server parts of the project. Open source software for chemoinformatics, bioinformatics, drug design, integrated together into one workflow At the moment: software for docking (modelling of the interaction between chemicals & proteins) and molecular dynamics. 5

© Digitalbiopharm Ltd All rights reserved. PROJECT 6 Biotargets 3D models or X-ray structures Molecular dynamics refinement with explicit solvent MODELS Virtual screening of chemical databases (ADME/Tox etc. filtered) Evaluation of protein-ligand complexes stability by high throughput molecular dynamics INITIAL BIOLOGICAL TRIALS, PRECLINICAL TRIALS BOINC SERVER Workflow of project INTERNET job results workunits

© Digitalbiopharm Ltd All rights reserved. IDEA OF THE PROJECT 7 Filter for toxicity - filter for huge databases including virtual chemical spaces QSAR, side effects Filter for pharmacokinetics Bioinformatics and OMICS data - selection of bio-targets Filter for toxicity - filter for huge databases including virtual chemical spaces QSAR, side effects Filter for pharmacokinetics Bioinformatics and OMICS data - selection of bio-targets Computational chemistry + Computational biology + Open code + Crowd + Our own digital currency = New level of pharmaceutics & biotechnologies Result - a lot of compounds which quickly pass preclinical and clinical trials Possibility to create multi-target drugs.

© Digitalbiopharm Ltd All rights reserved. Product and technology - Additional description of the technology: The method allows to solve the problems: experiments are simulated in virtual area. It is the fact that resources of modern computers / tablet computers / smartphones are in sleep mode and not used for the essential part of time. Volunteers/Crunchers/Miners give their computer resources (various motivations) and we obtain a scalable high-performance network. Segmentation of tasks into subtasks. Validation. 8

© Digitalbiopharm Ltd All rights reserved. These methods went out of date and they are inferior to experimental methods of high- throughput screening, or DNA-tag etc. Computer-based drug design, biofinrmatics and omics methods remain current. Statistics shows that the popularity of these methods grows up. However, today this process is not so fast as at the beginning of their use, or it is not so fast as in some other areas, e.g. in biostatistics. But our project also implies that analysis of huge OMICS data will be used for biotarget identification. Our project should be the most price-competitive comparing to any rivals in the area of preclinical trials. Answers to possible criticism 9 Methods are inefficient. In this case, it is most often referred to docking. Docking is effective not for the selection of prospective compounds, but for the sample enrichment, actually, it is one of the filters. At the output of this filter we will set more effective and resource-intensive methods, such as molecular dynamics, perturbation of free energy and thermodynamic integration. Volunteers may refuse to participate in a project with commercial results. Our experience shows that it is not true. We have hired thousands of computers in the first weeks of alpha testing. We also consider the possibility of using cryptocurrency and/or tokens (smart-contracts based) as payment.

© Digitalbiopharm Ltd All rights reserved. Cloud computing or clusters could replace volunteer computing. They can’t. Volunteer computing will always be cheaper. Volunteers absorb the overhead. Answers to possible criticism 10 Users replace notebooks and personal computers with smartphones. Smartphones are becoming more and more powerful, and they keep their battery charge longer and longer. Technology permits volunteer computing on smartphones. It is difficult to keep confidentiality while we use volunteer computing. Confidentiality is important for aggregate results only, and these results will be protected on the server. Because each work unit is very small, confidentiality is unimportant for intermediate results, but it likely still be kept due to huge volume of data.

© Digitalbiopharm Ltd All rights reserved. QSAR Relevance of the technologies of the project Moreover, the great part of publications in a number of core journals, such as J Med Chem, ChemMedChem include certain methods of computer modeling of drugs. By now, there is a lot of drugs which were developed using computer modeling methods. Talele T.T., Khedkar S.A., Rigby A.C., Successful applications of computer aided drug discovery: moving drugs from concept to the clinic. // Curr Top Med Chem. 2010;10(1):

© Digitalbiopharm Ltd All rights reserved. PC - protein with active ligand, NC - protein without ligand, o212 – ligand attitude Virtual screening using molecular dynamics 12 About 12 hours for GPU, for 1 compound. We are planning to get involved thousands of GPU. It provides the same speed as in high-throughput screening.

© Digitalbiopharm Ltd All rights reserved. Business model How does the project earn and plan earning? Creating new medicines (patents and royalty). Preclinical trials as fast as possible. Working by contract as Contract Research Organization (CRO). Leasing of the computer resources. Solving problems by request using crowd-sourcing (getting users of the platform involved). Distribution (the way to the final buyer): Direct B2B sales Life hacking: Crowd-sourcing for the portion of work in the areas of project development and forwarding. Search for polypharmacological (multitarget) drugs, a new, more promising paradigm. It is more difficult to use high-throughput screening for multitarget drugs creation. 13

© Digitalbiopharm Ltd All rights reserved. Publications 14 Our team completely agrees with this opinion: “One of the bottlenecks in bio-pharmaceutical innovation is biological screening. Virtual screening has been an attractive solution. MDVS can significantly improve the performance of a virtual screening campaign. Reducing HPC cost and increasing the computation speed will significantly accelerate biomedical innovation. There are no disease modifying drugs against for example Alzheimer's, osteoarthritis, metabolic syndromes and important cancers, MDVS campaigns described in this paper may shorten the time of pre-clinic studies for the disease modifying drugs, and anti-pandemic drugs.“ Source:

© Digitalbiopharm Ltd All rights reserved. Target groups Large, medium-sized and small pharmaceutical companies Academic research organization leading preclinical development of drugs 15

© Digitalbiopharm Ltd All rights reserved. Consumer and market 16 The final market of the project is the pharmaceutical R&D outsourcing market. The project will issue it with preclinical products (amount of money is 27 billions of dollars in 2014): contracts-in-rd-outsourcing-present-and-future). The perfect desirable scenario would be like that: Several hundred thousands of dollars in two years Several billions of dollars in 5-6 years Steady increase up to occupying a leading market position How far is the market competitive? The market is highly competitive with a pent-up demand though. Market share you are planning to occupy - this is difficult to forecast (perfectly % :-)). A minimum plan is any possible market share)).

© Digitalbiopharm Ltd All rights reserved. Business rivals. Who else is solving the same or an adjacent problem? 17 Technologically, the closest projects are и GPUGRID, which are nonprofit and not engaged in new drugs creation. The Project Performs docking of low-molecular compounds. It is closed. The docking proper is ща little avail. World Community Grid – mainly, docking. The GPUGRID Project uses GPU processors to model proteins and mechanisms of protein–ligand interactions. It is used for high-throughput molecular dynamics. It has good customer reviews. It has standing orders. Several hundreds of companies and research groups are working in the area of preclinical development of drugs in various countries. What are your advantages? The main distinction and advantage of our project is the complex approach to the development of drugs and presence of a great number of applications that allow to solve problems of computer design of drugs, molecular modeling and docking. We also aim at the analysis of genome sequences, usage of collective intelligence and crowd-sourcing for solving the broad range of the problems. Intrinsically, the project proposes to get great number of users involved into the process of drug creation.

© Digitalbiopharm Ltd All rights reserved. Current results SOFTWARE AND SERVER WERE SETUP 1 In previous version of our server molecular docking software Autodock and GROMACS were deployed on the server and compiled in the diverse operational systems environment. BOINC server was setup. VOLUNTEERS During Alpha test we got over 5000 PCs, which donated computational power to our project Current characteristics of the project: Current users: 1769 Current computers:

© Digitalbiopharm Ltd All rights reserved. Traction METRIC 1 The amount of users and expected resources. METRIC 2 Contract volume of R&D services (this includes obtaining grants and financing for the project from the state and from government contracts). METRIC 3 The amount of patents that are filled up and research papers published 19

© Digitalbiopharm Ltd All rights reserved. Development policy Creating a workflow Advanced: testing and validation of the methods, workflow in experiments for testing drugs Development of drugs by ourselves CRO: rendering a service in drug development and computer resources providing Key points in the project’s development (schedule plan) 20

© Digitalbiopharm Ltd All rights reserved. Team 21 Voronkov Andrey PhD in Chemistry, preclinical development of drugs Zaslavskiy Mikhail Independent consultant in data science and bioinformatics, he has a PhD in bioinformatics and more than 5 years of professional experience in industrial R&D Barinov Vladimir Programmer, DevOps, BOINC server administration specialist Sergey Ponomarev Blockchain specialist, Ethereum, Solidity, C/C++ programming

© Digitalbiopharm Ltd All rights reserved. Structure of expenses (investment required) Salaries (for server administrator and programmer, dev-ops is first of all) Server Marketing (it may turn out unnecessary - in case of viral dissemination of information) Costs 22

© Digitalbiopharm Ltd All rights reserved. Thanks for your attention! Distributed computing project Andrey Voronkov, PhD Skype: digitalbiopharmcom Phone: (United Kingdom) Address: Wenlock Road, London, N1 7GU 23