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Dealmaker Berlin 2017

Submission closed!

  • Close a potential project deal with Bayer
  • Attend the One-day matchmaking event
  • Pitch your startup and discuss possible projects

Calling all mature teams, startups and companies that have a solution ready to go! Our new Dealmaker is all about quality facetime between you and our experts for one full day.

If there is a match, we will invite you to Berlin to pitch your solution, discuss collaboration options and close a deal. Travel expenses are on us! Find out, if there is a mutual interest to start a bigger journey together!

We have put together specific challenges in which we are especially interested in solving with you! Applicants are asked to address one or multiple of these challenges below.  However, we are also open for other solutions that help healthcare providers or patients, as well as products dedicated to preventing or diagnosing diseases or improving pharmaceutical processes.

The Challenges:

Hemophilia

Empower hemophilia (bleeding disease) patients to individually adjust their treatment regimen to lead active lives. 

The current inability of hemophilia patients to independently assess their factor levels reduces spontaneity and results in less informed decision making regarding activity levels. Changes in activity and motoric range may be detected late or only in combination with major bleeds thereby creating a long term potential risk for patients´ health condition. For example:

Optimization of individual treatment is limited by an inability to track mobility and thereby better associate activity levels with bleeds. The ability to track and compare the mobility of patients intra-individually over time and against age matched non-hemophilia patients may be able to demonstrate the need for treatment beyond current minimal levels and could result in risk signals for future negative health outcomes for individual patients.

 

Women’s Health

Enabling earlier diagnosis of endometriosis.

Endometriosis is a chronic gynecological disease. It is estimated that 5-10% of all women of childbearing age are affected. Common symptoms are chronic pelvic pain, severe menstrual pain as well as pain during sexual intercourse. The disease is often associated with infertility. Currently it takes on average 7 years until the disease is diagnosed (usually via a minimal invasive surgery). Delayed diagnosis is due to low disease awareness (among women and doctors) and lack of non-invasive diagnostic tools. We are looking for solutions that help women and/or providers to diagnose the disease significantly faster.

Enhancing intrauterine device insertion training for providers.

Insertion of intrauterine devices is not part of the regular residency training in most markets. Initial training is usually provided by industry and intensified by practicing alone and/or with peers.  

Providing effective contraceptive counseling (face to face, remote or automated).

Contraceptive counseling many times is lacking knowledge of all available contraceptive methods, how they work and advantages/disadvantages. Women therefore often have information gaps on what would best suit their needs. A key reason is limited capacity on the provider side as he/she rarely is sufficiently reimbursed for contraceptive counseling and they don’t understand that women might experience dissatisfaction with the pill. We are looking for solutions that help women and/or providers to shorten the time & effort needed for full contraceptive counseling and lead to a detailed conversation on women’s contraceptive needs at the doctor’s office.

Improving comfort and experience during intrauterine device insertion for both providers & patients.

Women’s lack of knowledge about the procedure (insertion of intrauterine devices) may contribute to higher levels of perceived pain, which highlights the importance of counselling, and creating a trustworthy, unhurried and professional atmosphere in which the experience of the provider also has a major role; a situation frequently referred to as ‘verbal anesthesia’. We are looking for solutions that will help providers and/or women to better deal with the pain and/or improve the comfort related to intrauterine device insertion.

Simplifying the thread/placement check post-insertion of intrauterine devices.

Providers are asked to explain women how to check the removal threads to determine the correct location of an intrauterine device. This is currently done by feeling the threads with her fingertips. We are looking for solutions to simplify this process for women.

The Wow-Effect: A one stop solution to call attention on a product that treats acne and acts as a contraceptive.

Due to decreasing sales force resources and multiple needs of physicians there is a high need to identify digital solutions, means “Promotion 3.0”. Considering the life cycle stage of the products any digital approach should be tailored according to their specific needs e.g. launch brand, established product the solution should be clear, simple, easy to adapt, with low maintenance efforts, remind physicians 2-4 time a year and motivate them to prescribe.

According to the label we are not allowed to promote the product as a hormonal contraceptive. The Gynecologist is not focused on acne treatment but “the specialist” for hormonal treatments /contraceptives. The Dermatologist obviously treats acne but worried about hormonal treatments and its potential side effects e.g. VTE. He/she is not an expert in hormones like a Gynecologist.

 

Pulmonology

Improve identification of Chronic Thromboembolic Pulmonary Hypertension (CTEPH) patients.

As a rare condition with unspecific symptoms that are similar to those of Asthma, Pulmonary Hypertension (PH) in general and Chronic Thromboembolic Pulmonary Hypertension (CTEPH) in particular are very difficult to diagnose. There’s a significant amount of misdiagnosis & delayed time to correct diagnosis. Considering the link between PE & CTEPH and in light of the availability of big data, the delay in diagnosis could be reduced for the benefit of patients. Goal: Develop instruments/mechanisms to identify CTEPH patients earlier & more accurately.

Improve adherence for an oral pulmonary hypertension treatment.

Pulmonary Hypertension patients often suffer from comorbidities and are required to take other medications, which often have different dosing regimens or routes of administration. Since pulmonary vascular damage is irreversible treatment adherence is really key to ensure better patient outcomes. Goal: Increase time on treatment and reduce drop outs. Understand the individual challenges of disease management for patients to provide more customized treatment and care plans.

Innovative and efficient concepts for training staff to use a drug and device combination product in an intensive care unit setting.

User training is required for safe and efficient usage – How to effectively train Healthcare Practitioners (HCPs)  incl. critical care specialists, respiratory therapist, Intensive Care Unit (ICU) nurses and other hospital staff on an ICU drug and device combination product, without the need to train on site.

Create awareness for limited outcome of standard of care treatment for pneumonia in the hospital.

Education on challenges and treatment limitations when treating pneumonia in a hospital setting, in particular in the Intensive Care Unit (ICU). This could result in mortality, prolonged stay, extended recovery, longer intubation and ventilation, development of additional infections, prolonged treatment). Patients admitted to the hospital can acquire or arrive with pneumonia as a secondary disease leading to death or prolonged stay which in itself inherits risks. Treatment options are available, but have limitations leading to suboptimal outcome. How can we raise awareness and effectively communicate this? We are looking for creative and effective approaches in educating physicians in the ICU setting, Critical Care specialists, infection disease specialists and hospital formulary decision making bodies.

Identification of personalized and effective combination therapies for pulmonary hypertension patients.

As a progressing disease, pulmonary hypertension may require treatment escalation in form of a combination therapy. Medical therapy acting on three different pathways can be combined, combination is only possible across different pathways but not within the same pathway. New concepts are needed for identifying the most effective combination therapies based on the patient, e.g. considering implications of wash out periods and dose Titration.

 

Ophthalmology

Remote/mobile screening for Diabetic Retinopathy.

Here the challenge is to develop technology that allows wide field/ultrawide field images to be taken of the retina with a mobile device/smartphone that can then be interpreted remotely (e.g. using Machine Learning/Artificial Intelligence) as a screening approach for Diabetic Retinopathy (DR). Currently the images taken by smartphones are not sufficient for accurate diagnosis of DR with low levels of sensitivity and specificity. 

Remote monitoring of patients treated with anti-Vascular Endothelial Growth Factors (VEGFs).

Here the challenge is to develop technology/software that allows home-based/remote monitoring of a patient’s visual function in between clinic visits particularly in year 2 and beyond of treatment. The technology would need to be able to demonstrate a sufficient level accuracy of diagnosis of progression of disease so that patients may be able to return to the clinic earlier if the disease has progressed.

Utilizing real-world evidence (RWE) to predict the need for anti-Vascular Endothelial Growth Factors (VEGFs)-injections.

Currently we are unable to predict which patients may be able to extend their dosing interval in year 2 according to the label for a pharmaceutical product. An analytical approach to identifying relevant parameters that may allow clinicians to be able to predict those patients that can have their injection interval extended would help to deliver optimal outcomes whilst minimizing injection frequency.

 

Nephrology

Monitoring of chronic kidney disease (CKD).

Solutions for a better understanding of Chronic Kidney Disease (CKD) and thereby supporting the development of future treatments.

Diagnosis of acute kidney injury.

Solutions for a simple diagnosis of early Acute Kidney Injury in the hospital setting.

 

Artificial Intelligence

Prediction of combination therapies for cancer.

Computational in silico methods can be used to model the effect of compound combinations and to rank them for experimental validation. Current methodologies can perform significantly better than chance, but there is still a large gap between ground truth and the best prediction algorithms. Successful prediction of the effect of compound combination would be a break-through innovation in the field of oncology. Applicants should provide novel solutions with significant improvements compared to current approaches.

Extract compound structures and Structure-Activity Relationship (SAR) data from patents.

There have been several attempts in identifying compound structures from patents, but without high enough precision. In specific, differentiation of real compounds from building blocks, recognition of compound structures and mapping to experimental data is desired.

Computer-assisted identification of new compounds for protein targets.

Automated compound design including Machine Learning-based modeling, automated chemistry, miniaturized experimental affinity characterization in large panels of proteins and structure determination using Cryo-Electronmicroscopy (all in iterative cycles).

Develop analysis tool for in vivo experiments.

Developing Machine Learning-models to characterize all sorts of phenotypic read-outs of in vivo experiments (zebrafish screens, drosophila screens, tracking mouse/rat behavior).

 

Data Analytics

Data analysis tools to systematically identify worldwide activities in Research & Development.

Mining information from heterogeneous clinical databases and global information systems can be challenging. These data sources may be differently structured, semi structured or unstructured. Therefore mining the knowledge from them adds challenges to extract the required information efficiently. Relevant information is for example drug pipeline data and ongoing clinical trials which through analysis help identify trends in R&D. The challenge is to identify the right information from different databases in an efficient and effective manner by defining appropriate filters to pull out the most up-to-date and relevant information at any time.

Deep Learning Research Services for health and life science data.

We seek contract research organizations that are capable to provide research services around deep learning technologies in the health sector. This may need to be combined with capabilities to first curate, harmonize or standardize larger data sets semi-automatically. Capability to deal with diverse data types of the life sciences is key.

Transforming Electronic Health Records (EHR) data to analysis data sets.

Electronic Health Records (EHR) contain large amounts of information in poorly or completely unstructured formats. By contrast, analytical approaches (e.g. statistical learning, data mining) require highly structured (“tabled”) analysis data sets. To make real world data accessible for clinical research applications unstructured information has to be transformed into structured analysis data sets. The challenge is to develop a largely automated and reliable approach to the extraction of information from EHR and the transformation into high quality analysis data sets.

Analyze drug labels to generate new insights.

Analyzing drug product labeling, e.g. EU Summary of Product Characteristics and US Prescribing Information, across a therapeutic class or indication and associating label text with the source clinical data can provide valuable insights to inform drug development strategies and labeling content. Currently, this review requires significant time. The solution must analyze competitor labeling and answer questions related to content and the underlying evidence supporting the claims. It must also detect trends in new labels approved or changes to existing labels. Possible solutions could use artificial intelligence technologies such as natural language processing, machine learning, deep learning.

Develop efficient analysis of large scientific literature corpi to generate insights.

The goal is to extract information from a large literature database rapidly by e.g., generating automated thesauri (synonyms lists/ontologies) or visualizing the main topics (intelligent browsing).

How to implement prediction algorithms in hospital information systems.

Predictive Algorithm need to be implemented – One of the difficulties is the recognition of eligible patients for inhaled antibiotic therapy. Algorithms can help to identify the right patients based on big data. Assuming we would have a prediction algorithm for disease development and progression for pneumonia in the Intensive Care Unit (ICU). What would be the best way to implement such an algorithm/alert system in hospital processes/software systems?

Social Media use in pharma.

More and more customers are using Facebook, YouTube, Instagram, Twitter and other social media platforms on a daily basis. How can we utilize these technologies to make a successful awareness campaign, for example via Snapchat, but also stay compliant with rules and regulations. Be creative and be smart.

Medical knowledge platform for Pharmacists and/or General Practitioners.

Pharmacists and General Practitioners (GPs) are key in providing the best suitable healthcare treatments for patients. In their work routine, GPs need to quickly screen and identify common diseases and make treatment or referral decisions. Pharmacists fulfil or re-fill prescriptions and sometimes run the pharmacy business. During their work, both GPs and Pharmacists need to stay up-to-date with new developments in healthcare. What is needed is a platform/tool to easily access the latest relevant medical knowledge to help them serve patients with common disease screening and treatment identification.

 

Clinical Trials

Patient identification and recruitment for clinical trials.

Challenges in patient recruitment and enrollment in clinical trials are one of the primary causes for missing clinical trial timelines. The challenge is to help physicians and researchers to identify and recruit the right patients for their studies and plan in advance for a situation when multiple trials for the same kinds of patients may start in parallel, possibly creating contention and the need to triage. Also, the proposed solution/technology would help patients currently without treatment to get matched with more suitable clinical trials and thus get the chance for successful treatment. Multiple companies are involved in the logistics of trial recruiting, but how do we create an elegant solution for pharmaceutical companies to keep track of available and recruited patients across our trials, all while also adhering to applicable data privacy rules?

Improving the patient experience in clinical trials.

We want to explore a patient’s perspective of participating on a clinical trial, improving his/her experience and potentially even his/her health condition.

Develop a mobile platform for patients to report their health condition parameters.

Develop and validate an easy-to-use, secure, scalable, and efficient mobile platform for real-time data entry by patients in clinical trials – an electronic patient reported outcome mobile platform (ePRO), adhering to applicable data privacy rules.

Adherence improvement in (clinical trials OR) real life.

Patient non-adherence is a growing concern, as it is increasingly associated with negative health condition outcomes and higher cost of care, especially in chronic disease areas. There are many reasons for it, such as poor knowledge of the disease, inadequate perceptions of the need for treatment, forgetfulness, side effects and cost. A good solution probably requires a thorough understanding of the root causes of discontinuing treatment and knowing what a patient really wants. The solution should be a novel approach to improve adherence and ideally provide a clear win situation for all stakeholders involved (Patient, Pharmacy, Doctor, Pharmaceutical company, Insurer).

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Here's what's gonna happen next:

  • 1

    Submission — 01.04.2017 - 30.06.2017

    Submit your application until June 30th, 2017.

  • 2

    Evaluation — 01.07.2017 - 31.07.2017

    The challenge owners will go through the applications and take decisions.

  • 3

    Decision — 01.08.2017 - 01.08.2017

    Selected innovators will be informed.

  • 4

    Dealmaker Day — October 2017

    Selected innovators will be invited to Bayer in Berlin to finalize discussions about the potential collaboration project and sign a letter of intend.

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