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Bioanalytical software to battle against bacterial diseases

Devastating pathogen-borne diseases and plagues in nature, both viral and bacterial, have affected humans since the beginning of human history.

Until the mid-20th century, bacterial pneumonia was probably the leading cause of death among elderly people. Improved sanitation, vaccines and antibiotics, have all decreased mortality rates from bacterial infections, although the war against bacterial diseases has no foreseeable end.

A study developed by experts at ECDC (European Centre for Disease Prevention and Control) and the Burden of AMR Collaborative Group,(Study published in The Lancet Infectious Diseases for EU/EEA journal) estimates that about 33.000 european people die each year as a direct consequence of an infection due to bacteria resistance to antibiotics. Furthermore, the burden of these infections, is comparable to that of influenza, tuberculosis and HIV/AIDS combined (https://ecdc.europa.eu/en/news-events/33000-people-die-every-year-due-infections-antibiotic-resistant-bacteria)

Even though many bacterial infections can be treated successfully with appropriate antibiotics, antibiotic-esistant strains are beginning to emerge, according to the World Health Organization. The antimicrobial resistance is occurring everywhere in the world, compromising capability to treat infectious diseases, as well as undermining many other advances in health and medicine. Full impact is unknown, there is no system in place to track antibiotic resistance globally, and many modern medicines could become obsolete.

As a consequence, common infections might become deadly threats. Therefore an accurate medical diagnosis is imperative for correct treatment, and hence to drecrease mortality and reuce lenght of hospitalization.

A rapid diagnosis also allows for early streamlining of empirical antimicrobial therapies, thus contributing to limit the emergence and spread of antimicrobial resistance. The introduction of MALDITOF mass spectrometry (MS) for routine identification of microbial pathogens has profoundly influenced microbiological diagnostics, and is progressively replacing biochemical identification methods.

In this context, digital revolution provided relatively inexpensive and available means to collect and store data. Thereby, with the right data analysis, implementation of MALDI-TOF mass spectrometry, as well as exponential growth of databases, enable clinical laboratories a very rapid microbial identification at low cost.

These advances have been a decissive to reach to successful medical diagnosis for the early treatment of patients.

In 2015 a group of engineers and an analytical chemistry specialist (among them several PhDs in different fields and with a wide expertise) founded a bioinformatics company named CLOVER BioSoft, based on the Granada Health Technology Park, specialized in Bionalytical Chemistry data analysis and Microbial ID, using Mass Spectrometry. This team aims to giving solutions to real problems using knowledge-based approaches, understanding data and the statistics behind it.

Using methods of artificial intelligence, machine learning and big data analysis, was born this cutting-edge project: Clover MS Strain Typing, a software solution developed to perform research on bacterial analysis applications using MALDI-TOF MS.

The software AI-powered algorithms allows to build smart and reliable analysis of the bacterial strain typing by studying differences in the lipidomic profiles of bacterial strains, using Mass Spectrometry. Identifying bacteria at the strain level is particularly important for diagnosis, treatment and epidemiological surveillance of bacterial infections.

Each feature included is the result of close interaction with experts, to provide the most efficient and convenient workflow, in order to answer bacterial analysis questions. Among others, the software features include:

• Repeatability and reproducibility studies for the validity of biological and technical replicates.
• Antibiotic resistance analysis comparing with positive and negative controls.
• Feature extraction: Strain class, resistance mechanism, bacteria type, etc.
• Samples identification: Strain typing prediction with custom database support.

Project strength relies on its specifically designed data processing algorithm, as well as a patented lipid extraction method to provide competitive advantage, which is a complete protocol already proven and demonstrated in multiple applications. It also has the major advantages of MALDI-TOF MS (speed, cost-efficiency), with the addition of the gradual decrease in size, and thus cost of mass spectrometers.

Current bacterial ID systems in the market using MALDI-TOF MS are decreasing time and cost in the detection of bacterial species. Extending these systems to the identification of individual strains will help applying the most appropriate antibiotics for every patient, having a more accurate treatment and fighting against antibiotic resistance. Moreover, this ID systems in the coming future will help to predict unknown cases by learning known multivariate data patterns.

Participation in the ACTTiVAte program has been decisive to accelerate project, making possible to reach to current state of business model 100% validated, with a marketed ready product. In this sense, it has resulted highly important the advice received in ACTTiVAte on strategy and business planning, through mentoring and coaching dynamics. In addition to the funding received through ACTTIVATE and the SME Instrument, Clover Biosoft will make use of reserved funds and forecasted sales to face the expenses generated by this feasibility study. They will also raise private investment to complement these H2020 programs.

Some specific goals of the feasibility study are:

• Technical feasibility: Perform initial evaluation with our partner hospitals to assess the potential to become a clinical product. Develop a technical, regulatory and validation plan. In order to get first national and international sales orders during year 2019.
• Clinical feasibility: Identify the most severe pathogen strains causing most of the infections in European hospitals. Define the clinical validation strategy.
• Business opportunity: Discover the best approach-to-market strategy and establish a continuous presence on the field. Study real market needs, size and potential for profit and scalability.
• Economic feasibility: Detailed economic analysis to reach the clinical market.

Concerning the future, brilliant perspectives arises, since this system may have extensive applications in different sectors, such as industrial chemistry, environmental testing, food & beverage testing, as well other biotech applications such as mycobacterial ID, biomarkers for cancer, early detection of pressure ulcers and the Agrofood sector.

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