Currently, methodologies of human disease diagnosis are still far from capable of rapidly and accurately screening for multiple diseases, simultaneously in a large population, at affordable costs. MALDI-ToF mass spectrometry is an ultra-sensitive, ultra-fast and low-cost high-throughput technology which has a huge potential in clinical laboratory medicine
to achieve this goal. Such clinical analysis is starting the first steps towards human phenotype detection and hence phenomic
screening for multiple disease states. In this review, we will discuss the main advances achieved so far; putting forward targeted applications of MALDI-ToF mass spectrometry in the service of human disease detection. Here, we will focus mostly
on methodological workflow, namely MALDI-ToF data processing for phenomic analysis, using state-of-the-art bioinformatic pipelines and software tools. We will further focus on the role of mathematical modelling, machine learning and artificial intelligence algorithms for disease screening. Moreover, we will present some already developed tools for disease diagnostics and screening based on MALDI-ToF analysis. We will discuss the remaining challenges that are ahead when implementing MALDI-ToF into clinical laboratories. The move from identifying a normal to a single disease phenotype is
challenging, but the step towards simultaneously running multiple algorithms screens for multiple different disease phenotype may only be limited by computing power once the first hurdle is passed. The road map to reaching the full potential of
human clinical phenomics may be clearer than imagined and give an insight as to the huge benefits this technology may
bring for the future of diagnostics.