DENTAL IMPLANTS: DIFFUSION AND CLINICAL CHALLENGES

Dental implants are a highly successful and widely utilized solution in modern dentistry, with approximately 30 million procedures performed globally each year. The global dental implant market was valued at USD 5.11 billion in 2025 and is expected to reach USD 9.39 billion by 2034, with a steady annual growth (CAGR) of over 7%.

Despite the excellent long-term outcomes of implant therapy, with 10-year survival rates above 95%, technical and biological complications still occur in a significant number of cases. Among these, peri-implant diseases have emerged as a major clinical burden, with prevalence rates comparable to those of periodontal diseases. Approximately 50% of dental implants develop peri-implant mucositis, an inflammatory condition of the soft tissues surrounding the implant caused by bacterial plaque accumulation. Without appropriate intervention, mucositis can progress to peri-implantitis, a more severe disease involving both soft and hard tissues and potentially leading to implant loss.

Despite the high prevalence of these conditions, clinicians still face several limitations in their management. Currently, there are no reliable tools to assess disease severity or predict disease progression, and no therapeutic approach can guarantee complete resolution of mucositis or peri-implantitis. As a consequence, dental professionals lack standardised therapeutic protocols to follow.

THE PREBIOMICSPMT™ PROJECT

To address this challenge, the PreBiomicsPMT™ project, funded by the European Innovation Council (EIC) Transition Programme (Grant Agreement 101113004), builds upon several years of research conducted by the PreBiomics team on the role of the oral microbiome in peri-implant diseases (PreBiomics Beta Program, ERC Proof of Concept – PB3P). Through extensive microbiome studies performed prior to the project, PreBiomics researchers identified specific microbial signatures associated with peri-implant health, disease onset, and risk of progression, providing important biological insights into the microbial dynamics underlying peri-implant conditions.

Drawing from this scientific foundation, the PreBiomicsPMT™ project was launched with the objective of translating this knowledge into a practical clinical tool that can support dental professionals in everyday decision-making. The aim is to provide dental professionals with a system capable not only of supporting diagnosis and disease monitoring, but also of delivering personalized therapeutic recommendations based on each patient’s microbiological profile, ultimately improving the clinical management and longevity of dental implants.

To develop this system, we conducted a large multicenter prospective study involving over 110 dental clinics. Participating clinicians collected subgingival plaque and saliva samples, together with comprehensive clinical data, at two distinct time points: baseline and a 6-month follow-up. This longitudinal approach was essential for evaluating treatment efficacy and for assessing the effects of therapy on the peri-implant microbiome over time.

Over a period of two years, clinicians collected more than 6,000 biological samples, creating the largest datasets currently available for the study of peri-implant microbiomes.

TOWARDS PREDICTIVE AND PERSONALIZED IMPLANT CARE

Analysis of the clinical data confirmed the challenges associated with the management of these diseases. At the six-month follow-up, only 44.9% of mucositis patients showed complete disease resolution, while just 19% of peri-implantitis patients exhibited clinical improvement, results that are consistent with the current scientific literature. In more than half of the cases in both groups, the clinical condition remained stable with no significant improvement compared to the baseline diagnosis.

By integrating clinical information, patient history, and metagenomic microbiome data, the PreBiomics team developed a Decision Support System (DSS) capable of generating a ranking of therapeutic options based on their predicted probability of success for each individual patient. In parallel, we developed an advanced bioinformatic pipeline able to identify antibiotic and antiseptic resistance genes directly from complex microbiome samples. The system generates a resistance evidence report for molecules commonly used in dentistry, helping clinicians select the most appropriate antimicrobial therapy while minimizing the risk of ineffective treatment.
With PreBiomicsPMT™, treatment decisions can be guided not only by clinical experience or disease severity, but also by the individual microbiological profile of each patient. This approach increases the probability of therapeutic success, promotes more responsible antibiotic use, and contributes to a more effective long-term management of peri-implant diseases.